Morphometrics and processing yield of Cucumaria frondosa (Holothuroidea) from the St. Lawrence Estuary, Canada
Bibliographic record
Abstract
Sea cucumber Cucumaria frondosa have highly variable whole body mass and length, and are usually sold to Asian markets as dried gutted body wall. Understanding the relation between size and yield of dry product is essential for resource conservation and for economic purposes. In this study, stock-specific mass and length recovery rates were estimated for C. frondosa captured by dredging or diving at various depths and seasons on the South shore of the St. Lawrence Estuary, along Gaspé Peninsula, and processed in a commercial plant. The processing yield in dry product mass per sea cucumber was more than 1.5 times larger for sea cucumbers collected at 26-47 m depth compared to those collected at 9-16 m depth. Within each strata, there was little variation in the processed body mass, seasonally or spatially. Recovery rates based on gutted mass for this stock (13.4─14.5%) varied little among depths and seasons, despite observed seasonal and bathymetric variation in reproductive status. In contrast, recovery rates based on whole body mass and length were highly variable both seasonally and spatially. Stress related to dredging or post-capture handling induced important variable body contraction and water content, leading to variation in body length, mass and shape of sea cucumbers having the same processed body mass. Gutted mass was the best metric to predict processed body mass and to estimate size whereas whole body length was the least reliable. New stock-specific information on variability of body mass, length, and recovery rates induced by capture, and on seasonal and bathymetric variation in reproductive status and processing yields will be used for the design of future stock assessment surveys, and for stock conservation.
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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 | 0.000 |
| 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 | 0.000 |
| 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".