Dynamic adjustment of parental care in response to perceived paternity
Bibliographic record
Abstract
Theories of parental care evolution predict that genetic relatedness will be an important variable in the amount of care a parent provides. However, current inferences of relatedness-based parental investment from studies in humans and birds remain challenged. No study has yet demonstrated parental care adjustment in a manner uncomplicated by life-history correlates or experimental design. We now present a unique test that controls for individual life histories and demonstrates paternity-related dynamic adjustments in parental care. Brood-rearing male bluegill sunfish (Lepomis macrochirus) that are cuckolded to a varying degree will either increase or decrease their parental investment in response to changing information on paternity during brood development. Specifically, as parental males detect paternity lost to cuckolders and, hence, a reduction in the value of their brood, they adaptively lower their level of parental care. Conversely, if they detect that their paternity is higher than previously assessed, they adaptively raise their level of parental care. This dynamic adjustment during brood rearing indicates the importance of genetic relatedness in parental investment decisions and provides needed empirical support for theoretical predictions.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".