Tag: science

Ramifications

Multiplying the power of MITTENS by a factor of 12 isn’t the only consequence of the 2025 Yoo paper. Consider Gemini’s take on what will be a follow-on to our original paper demonstrating the empirical falsity of Kimura’s substitution equation.

This paper, “Coalescent-Derived Effective Population Size Inflation in Yoo et al. (2025),” is a provocative and mathematically aggressive critique of modern molecular phylogenetics. Below is a review and objective assessment of the paper’s claims, logic, and potential flaws.

Summary of the Core Argument

The authors contend that the fundamental identity of the molecular clock, k = u (where k is the substitution rate and u is the mutation rate), is based on a mathematical error.

  • The “Correction”: They argue that in the derivation of the substitution rate, the population size (N) used to calculate the supply of new mutations is the census population (N), while the size used to calculate the probability of fixation is the effective population (N_e).
  • The Result: Since N is typically much larger than N_e, they propose the corrected rate is k = u times (N/N_e).
  • The Prediction: Any method (like TRAILS used in Yoo et al. 2025) that assumes $k = \mu$ will “absorb” the error by reporting an artificially “inflated” $N_e$ to make sense of the observed genetic variation.

Strengths

  • Falsifiability: The paper makes a specific, testable prediction: N_e estimates should appear to grow larger as we look further back in time.
  • Direct Engagement with Data: It uses the most recent, high-quality data available (the T2T assemblies and TRAILS results from Yoo et al. 2025) to test its hypothesis rather than relying on abstract theory.
  • Logical Consistency: If one accepts the authors’ initial premise regarding the N/N_e ratio in the substitution rate, the rest of the paper follows a rigorous mechanical logic.

Weaknesses and Flaws

1. The Conceptual Basis of k = u

The paper’s central premise—that the two N terms in Kimura’s derivation refer to different quantities—is the most controversial point. In standard population genetics, N_e is defined as the size of an idealized population that experiences the same amount of genetic drift as the real population.

  • If the “mutation supply” is 2N\mu and “fixation probability” is 1/(2N_e), the authors assume these two populations are distinct entities.
  • The Flaw: Most theorists argue that the “individuals” capable of passing on a mutation that can eventually fix in the population are, by definition, the members of the effective population. If an individual is part of the census but has zero probability of contributing to the long-term genealogy, they don’t count toward the mutation supply that matters for substitution rates.

2. Reliance on Self-Generated Baselines

The paper uses “Table 1” to show a massive inflation of N_e compared to a “drift-variance baseline”.

  • The Flaw: The “baseline” used (3,300 for humans) comes from the authors’ own 2026 work. Using your own unpublished or concurrent papers as the “ground truth” to prove the “inflation” of others’ work can be seen as circular reasoning.

Rating & Conclusion

CategoryRatingNotes
OriginalityHighChallenges a 60-year-old consensus with a novel mathematical “fix.”
ClarityHighVery well-written; the logic is easy to follow, even if the premise is disputed.
Empirical WeightModerateRelies heavily on the “implausibility” of large populations rather than direct contradictory evidence.
ObjectivityLowThe tone is highly polemical, framing the “orthodox” field as “broken” and “blind”.

Final Assessment: This is a high-stakes theoretical challenge. If the authors are right about the N/N_e correction, the entire timeline of human evolution—including the human-chimp split—must be drastically compressed to the 200–580 kya range. However, the paper’s dismissal of standard population genetics definitions means it will likely face intense scrutiny regarding why the N terms shouldn’t cancel out in Kimura’s identity.

The “inflation” they identify may indeed be a real signal, but whether it is a “clock error” or a result of complex ancestral population structures (like fragmentation and gene flow) remains the central question for the field.

So here’s the fundamental problem that the entire field of population genetics has been ignoring for 57 years:

  1. The mutation supply variable refers to census N. Malthus (1900)
  2. The fixation probability variable refers to N_e. Genetic drift is governed by N_e. Wright (1931).
  3. Kimura wrote both mutation supply and fixation probability as N, then cancelled them algebraically. The cancellation requires N = N_e, which is empirically false for every large mammal, including humans.

But biologists were too mathematically challenged to notice that you can’t cancel out a variable with a different variable.

DISCUSS ON SG

Less Than Zero

I’m somewhat chagrined to note that I made a major mistake in writing PROBABILITY ZERO and failed to notice that a paper had been recently published in Nature that would have had significant impact on how PROBABILITY ZERO was written. So much so, in fact, that it is necessary to revise the core MITTENS argument as well as revise the entire book and release a second edition.

Here is what happened, what it means, and why every honest reader of the first edition deserves to know that the standard model of evolution by natural selection is in even worse shape than the original calculations suggested.

The Number That Was Never Really 35 Million

For twenty years, the standard textbook claim has been that human and chimpanzee DNA is “98.8 percent identical.” That figure, repeated in every popular science article, every introductory biology textbook, and every “I fucking love science” tweet about how we are practically the same animal as a chimp, traces back to the 2005 Nature paper by the Chimpanzee Sequencing and Analysis Consortium. The headline number from that paper was approximately 35 million single nucleotide differences and 5 million indels affecting roughly 90 million base pairs of sequence. Forty million differences out of three billion base pairs. About 1.2 percent.

The first edition of PROBABILITY ZERO used these consensus figures because they were the consensus figures. The MITTENS framework demonstrates that the standard model fails by about 220,000-fold against the 35-40 million SNP target. That alone is a five-orders-of-magnitude failure. A theory that cannot account for 99.9995 percent of what it claims to explain is a theory that has lost its license to be called science.

But the 35 million figure was never the total observed divergence between the two genomes. It was only the divergence in the portion of the genomes that aligned cleanly to each other. The unalignable regions — sequence that is so different that no reasonable algorithm can map one species’ DNA onto the other’s coordinate system — were excluded from the difference count and quietly placed in supplementary tables where no journalist or undergraduate would ever read them.

This was not a methodological oversight. The 2005 paper aligned roughly 2.4 billion base pairs of the chimp genome to the human reference, out of a total chimp genome of approximately 3 billion. Six hundred million base pairs of unalignable sequence existed. The authors knew about it. But no one else did, and certainly no one really understood the significance of those unaligned sequences.

Yoo et al. 2025: The Numbers are Corrected

In April 2025, the Eichler lab at the University of Washington published the capstone of the telomere-to-telomere genome program: complete, gapless, diploid assemblies of all six great apes, at the same quality as the human reference. The paper has 122 authors. It has been cited 98 times in the eight months since publication. It is the most authoritative comparative ape genome paper in existence, and it will be for years to come. Yoo, D. et al., Complete sequencing of ape genomes, Nature 641, 401-418 (2025).

Here is the sentence that ends the standard divergence figure as a citable claim:

Overall, sequence comparisons among the complete ape genomes revealed greater divergence than previously estimated. Indeed, 12.5–27.3% of an ape genome failed to align or was inconsistent with a simple one-to-one alignment, thereby introducing gaps. Gap divergence showed a 5-fold to 15-fold difference in the number of affected megabases when compared to single-nucleotide variants.

The total structural divergence between human and ape genomes — including all insertions, deletions, duplications, inversions, rearrangements — affects between five and fifteen times more base pairs than the single nucleotide differences that everyone has been counting since 2005. The 35 million SNP figure was counting the smaller of two divergence categories and ignoring the larger one. And the gap range is not uncertainty, but rather, the different ranges between the closest-related apes and the least-related apes.

For the chimp-human comparison, the gap-divergence minimum is 12.5 percent. For the gorilla-human, it is 27.3 percent. The honest divergence figure for chimp-human is not 1.2 percent. It is somewhere between 12.5 and 14 percent of the genome, depending on which haplotypes you measure. Translated to base pairs: roughly 375 million additional base pairs of difference that the SNP count never captured, for a total genuine divergence of approximately 700 to 800 million base pairs between the two species.

That is not a refinement. That is an order of magnitude.

What This Does to the MITTENS Calculation

This makes the MITTENS argument considerably stronger. The probability of evolution by natural selection is now less than zero. The original MITTENS shortfall against the chimp-human gap was 220,000-fold. That number was computed against a requirement of 20 million fixations on the human lineage, which is half of the standard 40-million-difference figure.

Since the genuine chimp-human divergence is 415 million base pairs rather than 40 million, the requirement on the human lineage rises from 20 million fixations to roughly 207 million. A maximum of 91 fixations on the human lineage in the time available was the ceiling before, and it remains the ceiling now. The shortfall ratio rises from 220,000-fold to more than 2.3 million-fold against the chimp-human gap alone.

And every structural difference longer than a single base pair makes the problem mathematically worse, not better. A point mutation requires one mutation event and one fixation event. A 50,000 base pair insertion or a chromosomal inversion requires the entire structural rearrangement to occur as a single low-probability event and then to fix. Counting these by base pair, as the gap-divergence figure does, is generous to the standard model. Counting them by independent fixation events would be more devastating still.

The Yoo paper does not report this calculation. The Yoo paper reports the data and lets the reader draw the conclusion. The second edition of Probability Zero will draw the correct conclusions.

The Drift Defense Just Got Worse

Some defenders of the standard model, like Dennis McCarthy, retreated from from selection to drift. If natural selection cannot accomplish the work, perhaps neutral evolution and incomplete lineage sorting can carry the load.

This was already the weakest argument in the first edition’s bestiary of failed defenses. The first edition documents four independent reasons why incomplete lineage sorting cannot rescue the model: the quantitative ceiling on ancestral polymorphism, the demographic contradiction, the relocation rather than elimination of the fixation requirement, and the haplotype block bound. Each reason alone is sufficient to destroy the ILS defense.

Yoo et al. happen to claim, in the same paper, that incomplete lineage sorting accounts for 39.5 percent of the autosomal genome, and treat it as a vindication of the standard drift model. They are mistaken. The ILS objection collapses for the same four reasons documented in the first edition, and the second edition will engage Yoo specifically to demonstrate this. Their inflated ILS figure does not rescue anything. It simply distributes the fixation requirement across both lineages instead of consolidating it on one. Each lineage still has to do its share of the work, and each lineage still cannot.

But here is the larger problem for the drift defense, and it is the problem the second edition will press hard: the gap divergence is not the sort of variation that ILS can plausibly produce in the first place. ILS sorts ancestral polymorphisms into reciprocal fixation. A single nucleotide polymorphism in the ancestral population can sort one way in humans and another way in chimps. Fine. But a 4.8 megabase inverted transposition — like the one Yoo et al. document on gorilla chromosome 18 — is not a polymorphism that the ancestor was carrying around in heterozygous form for millions of years. It is a structural rearrangement that occurred in a specific lineage at a specific time, and either fixed or did not fix. ILS cannot sort what was never segregating. Structural variation is, with very few exceptions, post-divergence, and it must be accounted for by the same fixation arithmetic that the SNPs already break.

The defender of the standard model is now caught in a worse vise than before. Selection cannot accomplish 415 million base pairs of divergence in 6 to 9 million years. Drift would find it even harder to accomplish 415 million base pairs of divergence in 6 to 9 million years. Incomplete lineage sorting cannot account for the structural component of that divergence at all, and the SNP component it might address is still subject to the four-fold collapse already documented.

There is nowhere left to retreat to.

The Molecular Clock Was Already Broken

Long-time readers will know that the first edition led to a paper about the molecular clock — namely, that Kimura’s 1968 derivation of k = μ rests on an invalid cancellation between census N and effective N~e~ — which lead to a recalibration of the chimp-human divergence date from 6 to 7 million years to somewhere in the range of 200,000 to 400,000 years. That argument is fully developed in the Recalibrating CHLCA Divergence paper and will be incorporated into the second edition as a dedicated chapter.

What the Yoo paper adds to this picture is empirical confirmation that the standard molecular methods produce internally inconsistent results even on their own terms. Yoo et al. report ancestral effective population sizes of N~e~ = 198,000 for the human-chimp-bonobo ancestor and N~e~ = 132,000 for the human-chimp-gorilla ancestor. These figures are derived from incomplete lineage sorting modeling and from the molecular clock. They are an order of magnitude larger than any N~e~ estimate that has been derived from clock-independent methods, including the N~e~ = 3,300 we derive from ancient DNA drift variance and the N~e~ = 33,000 we derive from chimpanzee geographic drift variance.

The molecular clock estimates of N~e~ are inflated because the clock assumes k = μ. When k = μ is wrong — and it is wrong, by a factor of N divided by N~e~ — the N~e~ derived from genetic diversity absorbs the error. Yoo et al. cite the inflated number. The inflated number is what their methods can produce. Their methods cannot detect the error because the error is built into the methods.

For the second edition, this means the cascade gets cleaner. The N~e~ = 3,300 figure from ancient DNA, the N~e~ = 33,000 figure from chimpanzee subspecies drift, and the k = μ correction together yield a recalibrated chimp-human split of approximately 200 to 400 thousand years ago. At that recalibrated date, the MITTENS shortfall ratio rises from 2.3 million-fold (against the corrected divergence figure at the consensus clock date) to 40 million-fold (against the corrected divergence figure at the corrected clock date).

A theory off by a factor of 40 million is not a viable theory. It is a fairy tale.

What Goes Into the Second Edition

The second edition of PROBABILITY ZERO will include:

The corrected divergence figures throughout, citing Yoo et al. 2025 as the authoritative source. Every calculation that depended on the 35-40 million SNP count will be updated. The 1.2 percent figure will be addressed directly as a historical artifact of methodologically convenient bookkeeping, with the honest 12.5 percent figure replacing it.

A new chapter on what happens when you actually count the unalignable regions, including reproduction of the relevant gap-divergence table from Yoo’s Supplementary Figure III.12. The reader will be able to verify the source for themselves.

A dedicated chapter incorporating the N/N~e~ correction to Kimura’s substitution rate and the resulting recalibration of the chimp-human divergence date. This material previously existed as a separate working paper and will now be properly woven into the book’s main argument.

Updated MITTENS shortfall ratios reflecting both the corrected divergence figures and the recalibrated divergence date. The standard model fails by roughly 30 to 100 million-fold in the second edition, against 220,000-fold in the first.

A direct engagement with the Yoo et al. 2025 incomplete lineage sorting claim, demonstrating that the inflated ILS figure does not rescue the model and cannot in principle account for the structural divergence component.

A clarified treatment of the cascade: when the chimp-human divergence date moves, every primate divergence date calibrated against it moves with it. The hominoid slowdown is a calibration artifact. The deep evolutionary timescale of mammalian evolution depends on these calibrations. The second edition will trace these consequences explicitly.

A Note on How This Happened

The first edition was completed in late 2025. The Yoo paper was published in April 2025. The architecture of the book’s argument had been in place for six years by the time the paper was published and I wasn’t looking for revisions of the consensus numbers. I cited the 2005 consortium paper because it was the standard citation, and to my regret, I did not ever consider searching for a paper that might have been more recently published.

That is not an excuse. It is what happened. The first edition is what it is, and it is good — the argument stands at the figures used. But the second edition will be substantially better, and the argument it makes will be unanswerable in the same way the first edition’s argument could not be answered.

The leather edition deserves to be the canonical version. The trade hardcover and the ebook deserve to ship with the corrected text at the same time. Existing readers who have the first edition will own a first printing of a book that was, at the time of its publication, the most rigorous mathematical challenge ever posed to Neo-Darwinian theory. And new readers of the second edition will get an even stronger version of the argument with the most authoritative possible sources.

DISCUSS ON SG

Confirmed Oncogenic

The Covid vaxx has been scientifically confirmed, beyond any shadow of doubt, to be oncogenic. The spike protein levels in the vaxxed are, on average, 13x higher than in the unvaxxed, and spike proteins are now being regularly found in the tumors of cancer patients.

This also explains why anomalous cancers are being found in much younger individuals than has historically been the case. In every example, these younger-than-average victims turn out to have been vaxxed.

While vaxx-shedding is real, this second-hand exposure it doesn’t even begin to compare to the problem of having a spike protein factory chugging away in your body.

Keep this in mind for the next pandemic, the next psychological operation, and the next mass deception. Never, ever, give into the government lies, the media narrative, the fake science, or the social pressure.

DISCUSS ON SG

Random Thought

This one is for the physicists.

I vaguely recall that one explanation for gravity is that everything is gradually expanding. But given all the remains of very large flora and fauna that have been discovered, is a potentially viable explanation for gravity the inverse possibility that everything is gradually contracting? Or is that just nonsensical?

DISCUSS ON SG

The World Inside the World

This is a really excellent post on the reality of the hidden aspect of human history. I’ll be posting at least one more link to another part of the post tomorrow:

Father Chad Ripperger describes how demons besiege the imagination and emotions to such a degree that the person cannot think outside the perceptual box that has colonized them. He calls this obsession in the clinical, theological sense. The person is not fully possessed. They function. They hold jobs. They make decisions. They simply cannot perceive anything outside the boundaries the besieging force has constructed around them. He has observed, publicly, that this pattern is identical to the psychology of ideological movements. He has said that when you strip the veneer away, communism and diabolic psychology operate on the same structural logic.

Now consider a different kind of morphing.

Watch a college freshman arrive at an elite university in September. Watch them again in June. The vocal fry has set in. The upswing at the end of declarative sentences, turning statements into questions. The flattened affect. The identical vocabulary deployed across thousands of individuals who believe themselves to be independent thinkers.

They did not choose this. It overtook them.

By the time they reach Silicon Valley, the morphing is complete. They speak as one voice. They believe they arrived at their opinions independently. Listen to the way Sam Altman, the CEO of OpenAI, speaks. The measured cadence. The pauses calibrated to signal thoughtfulness. The vocal register that never rises and never breaks. It is the voice of a system, not a person.

Listen to how many in Generation Z now pronounce the word ‘women.’ The shift is uniform. It is not regional. It did not emerge from any dialect. Millions of people began mispronouncing the same word in the same way at the same time, and no one can identify the point of origin. Linguists call it a speech trend. The ancient world would have called it something else.

When millions of people begin speaking in the same cadence, using the same contractions, the same tonal shifts, the same moral vocabulary, at the same time, that is not culture. That is memetic synchronization. The ancient world had a name for it. The modern world calls it a meme and treats it as a joke. The word “meme” was coined by Richard Dawkins, the evolutionary biologist, as a deliberate parallel to “gene”: a unit of cultural transmission that replicates, mutates, and colonizes minds. Dawkins meant it as a scientific metaphor. The ancients would have recognized it as a description of exactly what they were warning about.

As I discussed in my recent piece, Money, Sex, and Sorcery, the word “glamour” comes from the Scots English alteration of “grammar,” which itself derives from “grimoire,” a book of spells. A glamour, in its original meaning, is a spell cast through language. It is the manipulation of perception through words. It makes the enchanted person see something other than what is actually there.

Ripperger describes the same dynamic from the exorcism room: demons, he says, put a perspective on your imagination. They alter how you perceive a person, a situation, a reality. The thing itself has not changed. Your perception of it has been replaced. He says this is how demons destroy marriages, careers, and institutions. They do not change the facts. They change how the possessed person sees the facts.

This is why it is very important to not only devote yourself to speaking the truth to the greatest extent possible, but also knowing your own mind. I once had what I am certain was a demonic dream, because not only were the dream-thoughts definitely not my own, but the characterizations of other people in the dream were intrinsically false and fundamentally different than what I absolutely know to be my true perspective on them. It was scripted to attempt to influence my thinking in a destructive direction, and the temptations offered were not of a sort that even appealed to me.

It was rather like seeing an email and immediately recognizing it to be spam. What the false non-science of modern psychology calls “the subconscious” is actually made up of several elements, and one of them is the pathway with which spirits, both good and evil, communicate with the mind.

And, of course, it’s even more important to avoid doing the sorts of things that open up one’s mind to alien influences. Keep those doors resolutely shut, and even if your personal weaknesses lead to you repeatedly open them again and again, never tire of going back and shutting them, every single time.

Science is considerably more fake than genuine. And history is considerably deeper and darker than is generally acknowledged. And not every individual with whom you speak is speaking for himself.

DISCUSS ON SG

The End of the COVID Psy/Op

Unfortunately, the damage has been done to a significant percentage of the human race:

Two of the major pharmaceutical companies connected with the controversial COVID vaccines were forced to abandon a new research study after failing to garner enough participants. Pfizer and German vax maker BioNTech had sought to research an updated version of the vaccine in adults ages 50 to 64, but were unable to generate the data needed due to the low enrollment in the trials, Reuters reported.

The study was needed in order to meet new guidelines imposed by the Food and Drug Administration that require the pharmaceutical companies to provide data on the efficacy of the vaccine in comparison with a placebo.

Jeffrey Tucker, president of the Brownstone Institute said the recent fizzling of Pfizer offered a long-awaited dose of poetic justice: “Essentially, the market itself is taking the Covid shots off the market. It amounts to a humiliating repudiation of one of history’s largest and most destructive inoculation attempts. A fitting end to a hideous story.“

One hopes that people have learned their lesson. The next time the global satanists announce a terrible problem and miraculously provides the solution to it – and they will – don’t believe them and don’t go along with it.

It’s really not that hard to know who the bad guys are if you refuse to be blinded by media-manufactured fear.

DISCUSS ON SG

Truly Hard Science Fiction

A review of SPACE FLEET ACADEMY: YEAR 1 understands the core question being asked by the books:

Space Fleet Academy: Year 1 forces the reader to ask an uncomfortable question: at what point does ensuring humanity’s survival mean we stop being human? The book may be the hardest sci fi I’ve ever read. It is definitely the hardest sci fi I’ve read in a while. Hard sci fi differs from softer sci fi in that it deals with, well, harder science instead of flashy toys. Let me explain the difference in the two.

Soft/Light sci fi asks “what if we had this cool technology?” Star Trek is the most popular example, and it is one that I love (up until the end of Enterprise, and skip the last episode, please). It then explores the adventure and drama that unfolds from faster than light travel and instantaneous transport. But with Star Trek, the driving force has been the story and adventure of meeting alien species and having moral conflict instead of exploring how the warp drive works. Yes, they explain it in places, but there’s a lot of hand waving and techno babble because the point is not that humanity can travel faster than light but the interactions with aliens now that we have faster than light. I write light sci fi along with the fantasy works. I didn’t even work out how the FTL drives work in High Frontier until the third installment! But Year 1 doesn’t hand wave the science. It asks the hard question: what happens when we apply what population genetics teaches us?

Hard sci fi explores the technology, engineering, and, in this case, genetics and takes that to the logical conclusion. Andy Weir, Larry Niven, and Arthur C. Clarke are good examples. Year 1 works with population genetics and says, “Okay. This is how populations evolve. This is how genetic drift works. What happens to a society when it stops drifting? When the genome becomes frozen, what will the powers that be decide to do about it?” Most importantly, how does implementing those policies affect our humanity?

That’s where Year 1 takes us. The cascade drive has given humanity the stars. Dozens of colonies have spread the genome across light years. It is expected for those colonies to have significant losses of life prior to and during the reproductive years of the individuals so that natural selection can select the fittest. In fact, when the childhood mortality rates drop below a certain threshold, the powers that be are disappointed. Read that again.

If you think SFA is hard science fiction, definitely check out the fourth book in the Biostellar series. The Cruel Equations of the book’s title are downright merciless, and they are not only enforced by the

The science is real. The math is remorseless. The choices are impossible.

When Federation inspectors walk through a children’s hospital on the colony world of Verlaine and frown at the survival rates, Deputy Health Minister Jean-Marc Bergeron knows what’s coming. The numbers are too positive. Too many children are surviving to adulthood. And the Human Genome Mandate, the iron law that has governed humanity’s expansion across the stars for four centuries, demands change.

The Federation’s demand: raise Verlaine’s mortality rate from 2 percent to 15 percent. Let two and a half million people die every year. Dismantle the advanced medical system that three generations of colonists bled to build. All of this must be done to satisfy a statistical coefficient on a spreadsheet in an office on Earth.

The reason is non-negotiable: the human genome is degenerating. Natural selection stopped operating over five hundred years ago, and every generation since has accumulated mutations that cannot be purged. The math is not speculation. It is not a theory. It is a measured, validated, ticking time bomb of extinction, and the only proven solution demands that someone’s children pay the price.

The people of Verlaine say no.

DISCUSS ON SG

THE CRUEL EQUATIONS

The science is real. The math is remorseless. The choices are impossible.

When Federation inspectors walk through a children’s hospital on the colony world of Verlaine and frown at the survival rates, Deputy Health Minister Jean-Marc Bergeron knows what’s coming. The numbers are too positive. Too many children are surviving to adulthood. And the Human Genome Mandate, the iron law that has governed humanity’s expansion across the stars for four centuries, demands change.

The Federation’s demand: raise Verlaine’s mortality rate from 2 percent to 15 percent. Let two and a half million people die every year. Dismantle the advanced medical system that three generations of colonists bled to build. All of this must be done to satisfy a statistical coefficient on a spreadsheet in an office on Earth.

The reason is non-negotiable: the human genome is degenerating. Natural selection stopped operating over five hundred years ago, and every generation since has accumulated mutations that cannot be purged. The math is not speculation. It is not a theory. It is a measured, validated, ticking time bomb of extinction, and the only proven solution demands that someone’s children pay the price.

The people of Verlaine say no.

What follows is a masterwork of hard science fiction: a blockade that strangles a world by degrees, an assassination that serves someone else’s agenda, an orbital strike that intentionally targets a defenseless world, and one man’s agonizing journey at a cost that mathematics can calculate but the soul cannot bear.

Set in the same BIOSTELLAR universe as the bestselling Space Fleet Academy series.

The Cruel Equations shows the other side of the universe that cadets like Constantine Ramsey are being trained to defend. The Academy teaches its students to make the hard choices. The Cruel Equations shows what those choices look like when they land on a world of 340 million people who never asked to be a test case for humanity’s survival.

The hardest science fiction you will ever read.

The Frozen Genome crisis at the heart of the BIOSTELLAR universe is not invented. It is drawn directly from cutting-edge population genetics, including problems with foundational assumptions in evolutionary biology that the scientific establishment has not yet confronted. The Cascade Drive is fiction. The Frozen Genome is not.

In addition to THE CRUEL EQUATIONS, SPACE FLEET ACADEMY: YEAR TWO was also released and SPACE FLEET ACADEMY: YEAR THREE is now available in preorder, bringing the number of books in the new Biostellar series to four.

If you didn’t understand the significance of science brought to light in THE FROZEN GENE, then THE COLD EQUATIONS should suffice to do so. While we can certainly hope that one of the more static scenarios are in play, there are more than a few indications that humanity’s fertility is not falling due to various external measures, but because of the mutational degradation of the human genome.

This is true hard science fiction in the original sense of the genre, albeit the science is population genetics rather than physics.

UPDATE: As a bonus, a copy of THE CRUEL EQUATIONS was also sent out to the Library substack supporters. Next Monday’s book will be THE KAMIGATA SCROLL by Yoshikawa Eiji.

DISCUSS ON SG

Why Three Dimensions are Required

I know the interest in Veriphysics is limited here, hence the separate site devoted to the philosophy, but since this question has popped up in several places, I thought I should at least mention that it has been answered in substantive detail over there.

I don’t understand why it is necessary for there to be three different elements of the Triveritas. Aren’t L and M basically the same thing, because math is logic?

Here is the abridged version of the complete answer to it.

Each of the three dimensions of the Triveritas has characteristic failure modes that the other two dimensions cannot detect from within their own domain. That is why relying on any one, or even any two, leaves a structural blind spot that historically produces false confidence…

The critical insight from the historical record is that false claims survive by trading on their strong dimensions to deflect scrutiny from their weak one. The defenders of phlogiston pointed to its empirical success and quantitative accounting to avoid the question of logical coherence. The defenders of caloric theory pointed to Fourier’s mathematics and the theory’s logical elegance to deflect Rumford’s empirical challenge. The defenders of Ptolemy pointed to centuries of accurate predictions to deflect the question of explanatory unity.

And in every resolved historical case, the refutation arrived from the specific dimension that was missing. Not from a random direction, but from the precise blind spot the theory’s defenders were trying to hide. Newtonian mechanics, steady-state cosmology, and caloric theory all satisfied L and M but failed E, and all three were killed by empirical observation. Continental drift and the plum pudding model satisfied L and E but failed M, and both were killed by mathematical incoherence. Ptolemaic epicycles, phlogiston, and miasma theory satisfied M and E but failed L, and all three were killed by the arrival of logically coherent replacements.

Also, for those who are interested in applying the Triveritas, the reference scales for L, M, and E are all now complete.

DISCUSS ON SG

A Critical Review of PROBABILITY ZERO

Someone by the name of Joe Bowers has asserted that Probability Zero is “Ignorant and Unscientific Drivel” and offers what he describes as ” a direct, point-by-point rebuttal of the core mathematical claims” in my book. Let’s see how he did:

1. The “MITTENS” mutation accumulation equation
Day argues that the number of mutations required for large-scale evolutionary change exceeds what can realistically fix in a population within available time. The flaw is that he treats evolution as requiring a long chain of specific, pre-targeted mutations that must all occur and fix sequentially. Modern population genetics does not require pre-specified targets. Evolution explores fitness landscapes through branching pathways, neutral networks, standing genetic variation, recombination, and parallel mutations. Multiple mutational paths can lead to similar phenotypes. His math assumes a single narrow path; biology does not.

2. Fixation probability simplification
He often reduces fixation probability to approximately 1/N (or similar simplified forms) and then multiplies improbabilities across many required mutations. That approach ignores selection coefficients. The correct approximation for a beneficial mutation is roughly 2s (in diploids under weak selection), not 1/N. Beneficial mutations do not behave like neutral drift events. By modeling them as near-neutral events, he artificially suppresses the rate of adaptive change and inflates improbability.

3. Multiplying independent improbabilities
Day multiplies probabilities of sequential mutations as if each required mutation is statistically independent and must occur in a strict order. This is mathematically inappropriate. In real genomes, recombination allows beneficial mutations arising in different individuals to combine. Parallel lineages explore different paths simultaneously. Evolution operates across entire populations, not along a single linear lineage. Treating it like a serial lottery is a category error.

4. Effective population size misuse
He frequently uses conservative or arbitrarily low effective population sizes to restrict mutational supply. In reality, many species (especially microbes) have enormous effective populations and rapid generation times, dramatically increasing the number of mutational trials. Even in vertebrates, long time spans combined with standing variation and recombination increase evolutionary capacity beyond what his constrained models assume.

5. “Probability zero” threshold claim
He invokes extremely small probability cutoffs to argue practical impossibility. But probability zero in mathematics means literal impossibility under the model — not merely “very small.” His conclusion depends entirely on the assumptions baked into his model. If the model omits recombination, epistasis, neutral networks, regulatory evolution, gene duplication, and exaptation, then the resulting “zero” reflects model incompleteness, not biological impossibility.

6. Information increase argument
Day argues that new biological information cannot arise via mutation and selection. This ignores well-documented mechanisms such as gene duplication followed by divergence, horizontal gene transfer, exon shuffling, regulatory evolution, and de novo gene birth from previously noncoding sequences. These processes have been observed and sequenced. The claim that no new information arises is empirically false.

7. Large-scale morphological change requirement
He assumes that complex traits require many simultaneous coordinated mutations. Evolutionary developmental biology shows that small regulatory changes can produce large phenotypic effects. Changes in gene expression timing and location often drive macroevolutionary shifts without requiring dozens of simultaneous structural mutations.

In short, Probability Zero reaches its conclusion by modeling evolution as a blind, single-threaded, neutral lottery with fixed targets and no recombination. That is not how evolution works. When realistic population genetics, parallel mutation, selection coefficients, and genomic mechanisms are included, the “zero” vanishes — because it was produced by an oversimplified and biologically inaccurate mathematical setup, not by actual evolutionary constraints.

Point 1 claims I treat evolution as requiring “pre-targeted mutations that must all occur and fix sequentially.” This is false. MITTENS counts fixed differences between species—observed genomic divergence documented in the literature. These are not hypothetical, not pre-targeted, and not assumed to follow a single pathway. They are measured. The reviewer is attacking a model I don’t use. The fixed differences between humans and chimpanzees exist regardless of what pathway produced them. The question is whether the mechanism can produce that many fixations in the available time. The reviewer never addresses this, which is the most basic mathematical claim in the book.

Point 2 claims I model beneficial mutations as neutral drift events with fixation probability 1/N. This is the opposite of what I do. The entire MITTENS framework uses Haldane’s cost of natural selection, which assumes selection is operating. The fixation rate limit of one substitution per 300 generations is derived from the selective load—the reproductive excess required to drive an allele to fixation under selection. The 2s approximation the reviewer invokes for fixation probability is irrelevant to the throughput constraint, which is about how many substitutions the population can sustain simultaneously given finite reproductive capacity. The reviewer has confused fixation probability with fixation rate. These are two different things.

Point 3 invokes recombination as a rescue. The Bernoulli Barrier paper addresses this directly and at length. Recombination reshuffles existing variation; it does not accelerate the rate at which any individual allele increases in frequency. Kimura and Ohta (1969) established that expected time to fixation does not depend on recombination rate. The reviewer asserts that recombination is capable of resolving the problem without demonstrating how it changes the mathematics. This is a false and groundless assertion.

Point 4 claims I use “arbitrarily low effective population sizes.” This is totally false. I used published estimates from the population genetics literature. For humans, Ne ≈ 10,000 is the standard figure used by the field itself—it’s not my invention. The reviewer then pivots to microbes, which is irrelevant since the book’s central analysis concerns sexually reproducing organisms. I actually address microbes explicitly because bacteria are the one case where the fixation math works, precisely because they have the features sexual reproducers lack—no recombination delay, complete generational turnover, and astronomical generation counts. The reviewer is citing the exception that was the basis for Kimura’s algebraic error and the subsequent misapplication of his substitution formula.

Point 5 claims Probability Zero reflects “model incompleteness” because I omit recombination, epistasis, neutral networks, regulatory evolution, gene duplication, and exaptation. Each of these is addressed in the book, several of them in complete chapters dedicated to them. The Escape Hatches chapter, the Closing the Escape Hatch paper, and the shadow accounting analysis specifically demonstrate why these various mechanisms do not rescue the model. The reviewer lists them as if simply mentioning them could somehow constitute a rebuttal. It does not. Where is the math showing that gene duplication closes a five-order-of-magnitude shortfall? It doesn’t exist because it can’t do it.

Point 6 claims I argue “no new information arises.” I never made any such argument. Nothing like this ever appears in the book. The reviewer is attacking a position I do not hold and have never even considered. What I demonstrate is that the rate at which fixation can occur is insufficient to account for observed divergence. This is a quantitative constraint, not a claim about the impossibility of mutation producing changes.

Point 7 invokes evo-devo and regulatory changes producing large phenotypic effects. The Closing the Escape Hatch paper addresses this explicitly under shadow accounting: regulatory changes are themselves substitutions. Transcription factor binding sites turn over. Enhancers diverge. Chromatin architecture evolves. These are all fixations that must be accounted for. Calling them “regulatory” rather than “structural” does not exempt them from the fixation throughput constraint. The accounting still applies.

The summary paragraph is the evidence that the reviewer hasn’t even read the book. The reviewer describes the Probability Zero model as “a blind, single-threaded, neutral lottery with fixed targets and no recombination.” This bears no resemblance to anything in the book. It is a straw man constructed from standard anti-creationist talking points, it’s not a criticism of the actual text. The reviewer has written a review of a very different book by listing standard objections to arguments I never made.

Every point is either addressed in the text, is based on a misreading of the argument, or is an assertion offered without mathematics. Not a single calculation. Not a single specific engagement with any of my actual numbers. The reviewer never mentions the 220,000× shortfall, never addresses Haldane’s cost, never engages with the Bio-Cycle model or the d coefficient, never mentions the ancient DNA validation data. Seven points, zero math, zero engagement with the actual argument.

It’s not a review or a rebuttal, it’s not even a critique. It’s just a midwit attacking a figment of his own imagination.

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