Moulting synchrony in green crabs (<i>Carcinus maenas</i>) from Prince Edward Island, Canada
Bibliographic record
Abstract
The growth and spread of non-indigenous green crabs (Carcinus maenas) in Atlantic Canada is of concern to the sustainability of shellfish resources, particularly in areas recently invaded. Commercial green crab fishing has been initiated on Prince Edward Island to help control this species and provide a new resource for inshore fishermen. Developing a soft-shell crab product modelled after the Venetian ‘Moleche’ would provide an economic incentive beyond the existing hard-shell crab bait market. However, answers to questions such as the timing and characteristics of green crab moulting are required. A pilot study conducted in 2014–2015 collected seven groups of crabs and held them in individual compartments for 2–4 weeks to record moulting rates and physical characteristics. We found that a synchronized ‘moulting window’ occurs during July for male crabs. Field experiments in 2015 had an average moulting rate of 34%, with group-specific rates as high as 60%. The same cohort of crabs held in the laboratory had an average moulting rate of 48%, with group-specific rates as high as 75%. We observed a gradual increase in moulting rates from early to mid-July, after which all crabs caught had recently moulted, with evidence of new carapaces on all crabs. In 2015, the moulting window followed a 5°C increase in water temperature. Regarding morphology, the presence of a ‘halo’ on the episternites of the carapace was an indicator that a crab would soon moult. These promising results represent the first step in assessing the feasibility of a soft-shell, green crab industry.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".