Effect of culture depth on the shell thickness of the blue mussel <i>Mytilus edulis</i>: a practical case study comparing direct and indirect methods of measurement
Bibliographic record
Abstract
ABSTRACT Mytilus species have a fundamental role in coastal environments and constitute an important aquaculture resource. Their shell has a protective function and is affected by multiple factors, such as the size of the animal, density, environmental characteristics and presence of predators. It is crucial to accurately estimate shell thickness in order to understand the effects of the ever-changing environment on mussel physiology, morphology and ecology. This study compares a newly developed direct method for measuring shell thickness, using scanning electron microscopy (SEM), and a widely used indirect method (shell thickness index, STI), in the context of a practical case study of the blue mussel Mytilus edulis. In this study, STI did not appear as highly correlated to direct thickness measurement as in previous studies. This study also showed a weaker relationship between measured shell length and STI. In the case study, assessing the effect of culture depth on M. edulis growth and condition, STI showed a significant variation with depth, while SEM measured thickness did not. Therefore, the choice to use STI vs direct measurement of shell thickness drastically changed the results and interpretation of the case study. This work highlights the importance of a carefully designed method for measuring shell thickness and emphasizes that, before application, indirect methods should be quality controlled for the population studied. However, when high precision is needed for shell thickness measurements the application of SEM-based techniques may be necessary. This is the first study where SEM-based techniques have been used to measure shell thickness in M. edulis.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".