Novel Use of PIT Tags in Sea Cucumbers: Promising Results with the Commercial Species Cucumaria frondosa
Bibliographic record
Abstract
The lack of a reliable and innocuous mark-recapture method has limited studies that would provide essential information for the management of commercial sea cucumbers. Tagging sea cucumbers is notoriously difficult because of their plastic nature and autolysis capacities. The markers that have so far been tested, mainly on or through the body wall, were either lost rapidly or had major drawbacks (e.g. suitable only for batch identification, requiring complex analysis, causing infections, necrosis, behavioural changes and mortality). The present study explored the efficacy of passive integrated transponder (PIT) tags for individually marking sea cucumbers by assessing retention rates and long-term side effects of tags inserted in previously unstudied tissues/organs. Individuals of the species Cucumaria frondosa were tagged in the body wall, aquapharyngeal bulb and at the base of the oral tentacles. They were monitored closely for evidence of stress, infection, change in feeding and spawning behaviour and tag retention rate. Implanting the tag in an oral tentacle to reach the hydrovascular system of the aquapharyngeal bulb achieved the best retention rates in full-size individuals: from a maximum of 92% after 30 days to 68% at the end of the experimental period (300 days). Efficacy was lower in smaller individuals (84% after 30 d and 42% after 300 d). Following a slight increase in cloacal movements for 15 h post tagging, no side effect was noted in sea cucumbers tagged in the aquapharyngeal bulb via the tentacles. Feeding and spawning behaviours were not affected and no signs of infections or abnormal cell development in the vicinity of the tags were observed. This study indicates that marking sea cucumbers with 8.2 mm long PIT tags implanted via the oral tentacle is an effective technique, yielding relatively high retention rates over long periods without any detectable physiological or behavioural effects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".