Bibliographic record
Abstract
Females of many different species often mate with multiple males, creating opportunities for competition among their sperm. Although originally unappreciated, sperm competition is now considered a central form of post-copulatory male-male competition that biases fertilization. Assays of differences in sperm competitive ability between males, and interactions between females and males, have made it possible to infer some of the main mechanisms of sperm competition. Nevertheless, classical genetic approaches have encountered difficulties in identifying loci influencing sperm competitiveness while functional and comparative genomic methodologies, as well as genetic variant association studies, have uncovered some interesting candidate genes. We highlight how the systematic implementation of approaches that incorporate gene perturbation assays in experimental competitive settings, together with the monitoring of progeny output or sperm features and behavior, has allowed the identification of genes unambiguously linked to sperm competitiveness. The emerging portrait from 45 genes (33 from fruit flies, 8 from rodents, 2 from nematodes, and 2 from ants) is their remarkable breadth of biological roles exerted through males and females, the non-preponderance of sperm genes, and their overall pleiotropic nature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".