Systematic review and meta-analysis of PIT tagging effects on mortality and growth of juvenile salmonids
Bibliographic record
Abstract
Abstract A systematic review and meta-analysis was conducted to evaluate the appropriate tag:fish size ratio when tagging juvenile salmonids (generaOncorhynchus,Salmo, andSalvelinus). The review yielded 18 publications with 211 control and treatment groups reporting results from laboratory studies on the effects of passive integrated transponder (PIT) tags, plus a small number of additional studies on acoustic transmitters. A meta-analysis of the PIT tagging studies showed significant heterogeneity among studies with respect to mortality. Meta-regression revealed that juvenile salmonid mortality increased curvilinearly with the tag:fish length ratio, indicating that mortality risk is rapidly enhanced as smaller fish or larger tag sizes are used. The tag:fish length ratio effect on daily length or mass gain increased linearly. The results provide an estimate of the effects of the tag:fish length ratio on mortality and growth parameters in juvenile salmonids. Based on this, we suggest that researchers can follow best practices for tagging juvenile salmonids with tags that are not greater than 17.5% of fish total length (TL). This equates a minimum size threshold of 131 mm TL for tagging salmonids with 23-mm PIT tags, and 69 mm TL with 12-mm PIT tags. This information can assist researchers, managers, and welfare agencies striving to use the best possible evidence to make informed decisions regarding fish tagging.
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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 | 0.014 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.022 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".