Redefining and interpreting genomic relationships of metafounders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Metafounders are a useful concept to characterize relationships within and across populations, and to help genetic evaluations because they help modelling the means and variances of unknown base population animals. Current definitions of metafounder relationships are sensitive to the choice of reference alleles and have not been compared to their counterparts in population genetics—namely, heterozygosities, F ST coefficients, and genetic distances. We redefine the relationships across populations with an arbitrary base of a maximum heterozygosity population in Hardy–Weinberg equilibrium. Then, the relationship between or within populations is a cross-product of the form $${\Gamma }_{\left(b,{b}^{\prime}\right)}=\left(\frac{2}{n}\right)\left(2{\mathbf{p}}_{b}-\mathbf{1}\right)\left(2{\mathbf{p}}_{{b}^{\prime}}-\mathbf{1}\right)^{\prime}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>Γ</mml:mi> <mml:mfenced> <mml:mi>b</mml:mi> <mml:mo>,</mml:mo> <mml:msup> <mml:mrow> <mml:mi>b</mml:mi> </mml:mrow> <mml:mo>′</mml:mo> </mml:msup> </mml:mfenced> </mml:msub> <mml:mo>=</mml:mo> <mml:mfenced> <mml:mfrac> <mml:mn>2</mml:mn> <mml:mi>n</mml:mi> </mml:mfrac> </mml:mfenced> <mml:mfenced> <mml:mn>2</mml:mn> <mml:msub> <mml:mi>p</mml:mi> <mml:mi>b</mml:mi> </mml:msub> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mfenced> <mml:msup> <mml:mfenced> <mml:mn>2</mml:mn> <mml:msub> <mml:mi>p</mml:mi> <mml:msup> <mml:mrow> <mml:mi>b</mml:mi> </mml:mrow> <mml:mo>′</mml:mo> </mml:msup> </mml:msub> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mfenced> <mml:mo>′</mml:mo> </mml:msup> </mml:mrow> </mml:math> with $$\mathbf{p}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> </mml:math> being vectors of allele frequencies at $$n$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>n</mml:mi> </mml:math> markers in populations $$b$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>b</mml:mi> </mml:math> and $$b^{\prime}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>b</mml:mi> <mml:mo>′</mml:mo> </mml:msup> </mml:math> . This is simply the genomic relationship of two pseudo-individuals whose genotypes are equal to twice the allele frequencies. We also show that this coding is invariant to the choice of reference alleles. In addition, standard population genetics metrics (inbreeding coefficients of various forms; F ST differentiation coefficients; segregation variance; and Nei’s genetic distance) can be obtained from elements of matrix $${\varvec{\Gamma}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Γ</mml:mi> </mml:mrow> </mml:math> .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it