Use of length-based models to estimate biological parameters and conduct yield analyses for male Dungeness crab (<i>Cancer magister</i>)
Bibliographic record
Abstract
Length-based models were developed for the male Dungeness crab (Cancer magister) population on the Fraser delta near Vancouver, British Columbia. The models incorporate the probability of moulting, moult increments, natural mortality during moulting and non-moulting periods, direct fishing mortality, and handling mortality that occurs when sublegal-sized crabs are caught and released. The models were used to investigate how long-term yield might be affected by the combination of handling mortality and an intensive fishery. The models were calibrated to survey data, and key biological parameters were estimated. The probability of moulting is near one for male crabs in the 130- to 150-mm carapace width range and decreases as crabs get larger. There is a 70.1% probability a crab will survive the 1-month period beginning with a moult. The non-moulting natural mortality rate is 0.97 year1. When handling mortality is incorporated into the model, yield per recruit increases with the exploitation rate until it reaches approximately 94%. F0.1 is equivalent to 70%. An approach was developed to calculate the threshold ratio of discarded to retained crabs beyond which fishing would reduce the long-term yield.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".