TOLERATED CO-FEEDING IN RELATION TO DEGREE OF KINSHIP IN JAPANESE MACAQUES
Bibliographic record
Abstract
Abstract We analyzed co-feeding in relation to degree of kinship in Japanese macaques Macaca fuscata), testing experimentally five categories of matrilineal kin dyads: mother-daughter, grandmother-granddaughter, sisters, aunt-niece and nonkin. In each test, two adult females with a clear dominance relationship had access to a box containing a limited quantity of highly prized food. The dominant female could easily prevent the subordinate from eating so that food was easily monopolizable, hence the use of the expression tolerated co-feeding. Rates of tolerated co-feeding increased steeply with degree of kinship. The aggression levels of dominant females towards subordinate females decreased with increasing degree of kinship and this effect was most apparent between mothers and daughters. The confidence level of subordinate females increased with degree of kinship and this effect became apparent above the aunt-niece kin class. Prior access to food by the subordinate female was a significant means of access to food, mostly beyond the grandmother-granddaughter kin category. The results point to a relatedness threshold for the preferential treatment of kin at r = 0.25 (grandmother-granddaughter and sister dyads), beyond which (r = 0.125: aunt-niece dyads), levels of tolerated co-feeding were comparable to those of nonkin females. The identity of this threshold with that found in previous studies on the same group for two different types of interactions suggests the existence of a generalized relatedness threshold for kin favoritism in Japanese macaques. Assuming that the costs of food defense by the dominant females were negligible and that tolerated co-feeding was altruistic, our results support the role of kin selection in the evolution of altruism in primates beyond the mother-offspring bond.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".