Logistic regression approach to modelling the variability of recombination rate
Bibliographic record
Abstract
The objective of the paper is to quantify the relationship between recombination rate and factors such as ‘sex of sperm’, paternal halfsib family, and individual, using logistic regression modelling. The analysed data set consists of 2214 single bovine sperm cell samples. Haplotypes at each single sperm were determined at eleven marker loci forming eight intervals located on chromosomes 6, 23 and X/Y. The experimental design comprises six paternal halfsib families. Six logistic regression models are fitted to the data from each interval. Departure from commonly assumed homogenous recombination is detected for one marker interval on chromosome 23 – influence of individual and ‘sex of sperm’ by family interaction, and for both intervals mapped to sex chromosomes – influence of ‘sex of sperm’ and paternal halfsib family.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".