Thermal games in crayfish depend on establishment of social hierarchies
Bibliographic record
Abstract
An unequal resource distribution is commonly seen in dominance hierarchies, in which the individual with the higher status is more successful in obtaining the resource. One possible resource is preferred temperature. When situations allow, ectotherms regulate their body temperature by behaviourally selecting different environmental conditions, achieving, when possible, a preferred temperature. Using a shuttlebox, the preferred temperature for Procambarus clarkii was determined to be 23.9°C with upper and lower voluntary escape temperatures of 25.9 and 21.8°C, respectively. If this preferred temperature zone (21.8-25.9°C) was valued as a resource, given the choice between a preferred temperature and a non-preferred temperature, crayfish should compete over the preferred temperature, with the dominant individual of dyadic pairs achieving the preferred temperature more often than the subordinate. Using a dual-choice experimental tank, competition over a binary temperature choice between rank-established paired crayfish was determined under both warm and cold challenge conditions (warm vs preferred temperature and cold vs preferred temperature, respectively). In naive pairings, similar levels of competition over the preferred temperature occurred in both warm and cold challenge trials, as predicted by game theory. In established pairings, however, dominant crayfish gained significantly greater access to preferred temperature in both warm and cold challenge conditions. These results demonstrate that crayfish engage in a cost-benefit assessment during their initial agonistic contests over temperature, but as hierarchies mature, these thermal games are decided by the dominant animal gaining primary access to the temperature resource.
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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 | 0.000 | 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 | 0.001 |
| 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".