Field test of a new method for tracking small fishes in shallow rivers using passive integrated transponder (PIT) technology
Bibliographic record
Abstract
A new method for tracking small fishes in shallow streams based on passive integrated transponder (PIT) technology, using a portable reading unit, was investigated. The device consists of a chest-mounted palmtop computer, a reader, and a 12-V battery enclosed in a backpack, connected to a 60-cm-diameter coil antenna mounted on a 4-m-long pole. The method was field tested with wild Atlantic salmon, Salmo salar, parr using transponders 23.1 mm long and 3.9 mm in diameter surgically implanted in the peritoneal cavity of the fish. Laboratory experiments indicated no posttagging mortality for fish > 84 mm in fork length and no tag loss when sutures were used. In the field, tag detection distance was up to 1 m. While moving the antenna above the stream surface, the operator could locate a fish's position to within a square metre. Experiments indicated that more than 80% of tagged parr, on average, were detected by the reader. The technique is a useful alternative to standard radiotelemetry in small-scale environments because PIT tags can be implanted in smaller-bodied fishes and fine-scale movements of individuals can be studied. It can be applied to address numerous questions in the fields of animal behaviour, habitat use, and population dynamics.
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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 | 0.001 |
| Open science | 0.001 | 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".