Reporting and shedding rate estimates from tag-recovery experiments on Atlantic cod (<i>Gadus morhua</i>) in coastal Newfoundland
Bibliographic record
Abstract
It is important to have good estimates of tag reporting rates when inferring exploitation rates and other mortality rates from tagging experiments. We estimate the reporting rates of single- and double-tagged Atlantic cod (Gadus morhua) caught in commercial fisheries around coastal Newfoundland, Canada, based on an extensive series of multi-reward tagging experiments conducted during 1997–2004. Reporting rates for single-tagged cod varied from 58% to almost 100%, with significant temporal and spatial variability. The odds of reporting a double-tagged cod was almost double that of a single-tagged cod. Returns from double-tagged cod allow us to estimate tag shedding rates. Tag shedding rates suggested that 22% of fish lost their tag during their first year at liberty; subsequently, tag shedding rates were much lower (<10%). We also found that twice as many fish lost tags when the tags were attached anteriorly at the base of the first dorsal fin compared with a position more towards the posterior end.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".