Direction, ontogeny, and mechanism of the temperature-size rule operating in a large marine crab, <i>Chionoecetes opilio</i>
Bibliographic record
Abstract
Abstract The classic temperature-size rule (TSR) states that ectotherms mature smaller in warmer than in colder conditions; the reverse TSR is the opposite response. We combined field observations with laboratory experiments and published information to synthesise the response of snow crab (Chionoecetes opilio), a marine brachyuran with determinate growth, to temperature. Size at onset of physiological maturation/maturity and after terminal moult (TM) were positively related to temperature, thus indicating the reverse TSR. Moult increment varied little with temperature, but crabs were larger at instar in colder than in warmer water due to an initial difference in settlement size that propagated to higher instars, suggesting classic TSR prior to settlement. The pattern of increasing TM size with temperature was caused by crabs moulting more times before TM in warmer than in colder water. Intermoult period (IP) declined exponentially with temperature, and lower instars were more temperature sensitive than higher instars. Temperature effects on IP were strong enough to explain changes in size and instar number at TM under a possible time-invariant maturation schedule. Skip moulting was observed in the smallest crabs reared in the laboratory and resulted in high mortality. The reverse TSR in snow crab seems to be adaptive to coping with ectotherm predation.
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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 | 0.000 |
| 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".