Prospective evolutionary drivers of allocare in wild belugas
Bibliographic record
Abstract
Abstract Allocare, investment in offspring from non-parents, poses an evolutionary enigma. While the fitness trade-offs driving parental care are universal, alloparents may be driven by kin selection, reciprocation, the need to acquire parenting skills (‘learning-to-parent’), an indiscriminate attraction towards infants (‘natal attraction’), or a combination of multiple drivers. Among belugas ( Delphinapterus leucas ), allocare has been reported in wild and captive populations, but its underlying mechanisms remain untested. Using over 1800 focal observations, we quantified alloparental associations in St. Lawrence Estuary (SLE) belugas to determine whether the learning-to-parent and natal attraction hypotheses are consistent with patterns of allocare in this population. We found that subadults showed little interest in providing allocare and that alloparental investment remained constant across offspring age classes. As the observed patterns of allocare are inconsistent with both the learning-to-parent and natal attraction hypotheses, allocare in SLE belugas is likely driven by kin selection, reciprocation, or a combination thereof.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".