American lobster Homarus americanus demographics related to depth and temperature in lobster fishing areas 33 and 34 off Nova Scotia
Bibliographic record
Abstract
The lobster fishery is the most valuable fishery in Canada, representing over 40% of total seafood landings, with most landings in lobster fishing areas (LFAs) 33 and 34 off Nova Scotia. Canadian lobster landings have been steadily increasing since the 1980s and are projected to continue to increase due to fewer predators and expanding suitable habitat. Within LFAs, lobster are caught up to 90 km from shore. Differences in morphological characteristics between inshore and offshore contingents (if they exist) remain poorly identified and characterized. This study characterized lobster morphometrics, population structure, and other metrics of population status in relation to habitat characteristics of depth and temperature in LFAs 33 and 34 to determine if lobster contingents exist and if so, their relationships to local habitats. Overall, relationships were apparent between lobster morphometrics and environmental factors including depth, bottom temperature, surface temperature, month, soak time, latitude, longitude, and between the lobster morphometrics and lobster condition, sex, carapace hardness, and carapace length. Most environmental variables were collinear, obscuring any significant relationships in all models. Furthermore, deviance explained was low for all GAMs and misclassification rates were high for nearly all multinomial logistic regressions, demonstrating that the models were able to account for little variability in the data. Our results were generally comparable to other studies with a few discrepancies. In conclusion, eliminating the collinearity between variables and recording video footage of lobster at depth would allow us to strengthen our analyses and consider potential differences in lobster behaviour. We did not determine if local contingents exist in the inshore and offshore regions of LFAs 33 and 34 because generalizing habitats to inshore and offshore regions fails to capture habitat characteristics at finer scales of resolution that may affect lobster distributions.
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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 | 0.000 | 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) | 0.002 | 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".