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
| Category | Rating | Notes |
| Originality | High | Challenges a 60-year-old consensus with a novel mathematical “fix.” |
| Clarity | High | Very well-written; the logic is easy to follow, even if the premise is disputed. |
| Empirical Weight | Moderate | Relies heavily on the “implausibility” of large populations rather than direct contradictory evidence. |
| Objectivity | Low | The 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:
- The mutation supply variable refers to census N. Malthus (1900)
- The fixation probability variable refers to N_e. Genetic drift is governed by N_e. Wright (1931).
- 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.