Bibliographic record
Abstract
Genotypically, all offspring are created equal, but maternal manipulations of phenotype can render some offspring more equal than others (e.g. differences in egg size or composition, hormonal titre or hatching interval). A phenotypic handicap results when such variation impairs an individual’s competitive status. Here we examine both the causes and consequences of manipulations of such phenotypic handicaps. Hatching asynchrony is the primary handicap; differences in egg size and hormonal manipulations play secondary roles, unless offspring hatch synchronously. Begging strategies are role-dependent: last-hatched marginal offspring generally beg harder, but receive less food than earlier-hatched core offspring, consistent with phenotype-limited models of begging behaviour. There are alternative, though not mutually exclusive, explanations for such behaviour. Smaller nestlings may simply be hungrier, or influenced by different hormonal titres. Future work should focus on role-dependent begging strategies, such as whether marginal nestlings modulate their begging effort according to thei prospects of winning.
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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 | 0.000 |
| 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) | 0.003 | 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 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".