Refining age at legal-size estimation in the Newfoundland & Labrador populations of the snow crab <i>Chionoecetes opilio</i> (Fabricius, 1788) (Decapoda: Brachyura: Oregoniidae)
Bibliographic record
Abstract
Abstract Current knowledge of age at legal size in Newfoundland & Labrador (NL) and other snow-crab stocks is incomplete due to historic estimations not accounting for skip-molting growth delays. Previous work has shown skip-molting incidence to occasionally be very high in males, both in NL and some other major snow-crab stocks. This warrants research to better understand impacts of skip-molting on snow-crab age and growth dynamics, which are central to population assessment and resource management. We simulated the impact of skip-molting on growth dynamics of snow crabs from three regions around NL by coupling a nineteen year time series of molt-type probabilities derived from field trawl surveys to historical data on age-at-instar based on cohort analysis of wild populations that do not consider skip-molting in making age estimations. Trawl surveys and simulations showed that skip-molting is a prominent feature in NL snow crabs, with up to four skip-molts being a reasonable maximum possible estimate for males in portions of the NL snow-crab stock. A complementary analysis examining the ability to age snow crabs using gastric mill band counts showed overall strong agreement with published growth trajectories that were modified to include skip-molting as well as reasonable average age approximations for most crabs, but unexpectedly high variability in age estimates for individuals of a same instar stage and unexpectedly low age estimates for younger crabs. Our study leads to a refinement of age at legal size for NL snow crab from the current nine-year estimate to a range of 9–13 years. Although this range is deemed to capture virtually every crab reaching legal size in NL snow-crab populations, ages higher than 11 years to fishery recruitment (2 skip-molts) are relatively infrequent.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".