Data from: Kin recognition in guppies uses self-referencing on olfactory cues
Bibliographic record
Abstract
Kin recognition plays an important role in social behavior and evolution, but the proximate mechanisms by which individuals recognize kin remain poorly understood. In many species, individuals form a “kin template” that they compare against conspecifics’ phenotypes to assess phenotypic similarity–and by association, relatedness. Individuals may form a kin template through self-inspection (i.e. self-referencing) and/or by observing their rearing associates (i.e. family-referencing). However, despite much interest, few empirical studies have successfully disentangled self- and family-referencing. Here, we employ a novel set of breeding crosses using the Trinidadian guppy (Poecilia reticulata) to disentangle referencing systems by manipulating exposure to kin from conception onwards. We show that guppies discriminate among their full- and maternal half-siblings, which can only be explained by self-referencing. Additional behavioral experiments revealed no evidence that guppies incorporate the phenotypes of their broodmates or mother into the kin template. Finally, by manipulating the format of our behavioral tests, we show that olfactory communication is both necessary and sufficient for kin discrimination. These results provide robust evidence that individuals recognize kin by comparing the olfactory phenotypes of conspecifics against their own. This study resolves key questions about the proximate mechanisms underpinning kin recognition, with implications for the ontogeny and evolution of social behavior.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.015 |
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".