Trap‐based indicators of egg production following increases in minimum legal size in <i>Homarus americanus</i> fisheries
Bibliographic record
Abstract
Abstract Minimum legal size (MLS) is an important conservation measure in trap fisheries for Homarus americanus. MLS has increased in several management areas in the Canadian Maritimes since 1987. A key conservation objective has been to increase egg production, with predictions of the effects of MLS increase based on egg‐per‐recruit models. We evaluated whether expectations of increases in ovigerous females (OF) were realised when MLS was increased. Data were examined from at‐sea samples of the commercial trap catch from 11 ports from 1986 to 2003. OF indicators were developed based on the OF catch‐per‐unit‐effort (CPUE) of different sizes, and on the percentage (PCT) of females that were ovigerous. Because there were within‐season increases in CPUE and PCT, annual indicators were based on regressions of CPUE on day in the season. There was considerable variability in all the time series of OF annual indicators and any effects of smaller MLS increases could not be detected. Increases in OF indicators were evident in areas that undertook the largest MLS increases (6–6.5 mm CL).
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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 | 0.002 |
| 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".