The catchability of large American lobsters (<i>Homarus americanus</i>) from diving and trapping studies off Grand Manan Island, Canadian Maritimes
Bibliographic record
Abstract
Catchability (q) in traps was estimated for American lobsters (Homarus americanus) in Flagg Cove, off Grand Manan Island (New Brunswick, Canada), where large females (>100 mm carapace length (CL)) aggregate in late summer and early fall. In 2001 and 2002, diver surveys were used to estimate lobster density, and traps were then deployed to obtain catch rates. Bayesian generalized linear models were fit to the densities of different size groups (81–100, 101–130, 131–160, and >160 mm CL) of ovigerous females, non-ovigerous females, and males. Catchability was strongly affected by year. Differences in q due to sex and size for ovigerous females, non-ovigerous females, and males were apparent but were not consistent between years. Size was not an important factor for the catchability of lobsters between 81 and 160 mm CL. In comparison with lobsters of a similar size in other areas, Flagg Cove lobsters in the size range of 81–100 mm CL were less catchable. We hypothesize that this resulted from the high densities and larger sizes of lobsters in Flagg Cove, which likely lead to increased agonistic interactions and reduced entry of lobsters into traps.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".