Social memory and quantity discrimination: A cross cichlid species comparison.
Bibliographic record
Abstract
Cooperation is a highly complex social interaction that often requires coordination and communication between two individuals. Reciprocity is one explanation for how cooperation evolves and is maintained; help now will eventually be repaid in kind. For reciprocity to work, individuals must be able to differentiate between those who helped previously versus those who cheated. However, there is little empirical evidence that cooperative species have an enhanced recognition capacity compared to noncooperative species. Here we conducted a comparative study to address this question using three cooperatively breeding cichlids and three of their close relatives that are not cooperative breeders, all from Lake Tanganyika. In a first experiment, we offered fish a choice between spending time with a familiar versus an unfamiliar conspecific and found that while cooperative cichlids spent more time with familiar individuals, the noncooperative cichlids spent more time with unfamiliar individuals. In a second experiment, we provided a choice between affiliating with one versus three individuals (all unfamiliar) and found that 2/3 cooperative and 3/3 noncooperative cichlids strongly preferred to affiliate with larger groups. Our results suggest that both cooperative and noncooperative cichlids have evolved the ability to recognise familiar individuals and have affiliative preferences; however, the nature of these preferences differ. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".