Temperature-dependent growth of the blue crab (<i>Callinectes sapidus</i>): a molt process approach
Bibliographic record
Abstract
Crustaceans display discrete and biphasic growth as a result of the molting process, so the traditionally used von Bertalanffy growth model does not capture well the phenomena associated with molting-based growth. A molt-process model can predict crustacean growth, including the temperature dependence of intermolt period that can produce the extended overwintering phenomena during which growth ceases. This study parameterized a molt-process model for the blue crab (Callinectes sapidus; Portunidae). Crab growth histories were observed for individual crabs held in field enclosures and temperature-controlled, recirculating tanks. A growth-based temperature of torpor (T min ) of 10.8 °C was determined. A mean growth per molt of 119.5% increase in carapace width was observed. The average intermolt period observed was 536 ± 231 degree-days. The predictive ability of these growth parameter estimates was evaluated against growth observed in the field based on data on interannual changes in size frequencies of crabs from a winter dredge survey. The evaluated model was used to explore recruitment timing in warm (1996) and cold (1998) years. A 10% shift in the timing of juvenile crabs becoming available for legal exploitation was predicted from the simulations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".