Evaluation of survival estimates generated from tracking downstream migrating juvenile sea lamprey (<i>Petromyzon marinus</i>) with a miniature acoustic telemetry tag
Bibliographic record
Abstract
Fish that undertake juvenile migration pass through habitats that vary in mortality risk. The ability to identify regions of persistently low survival would improve fishery management. We conducted a field study combined with predictive modeling of survival in downstream migrating juvenile sea lamprey using a new micro-acoustic telemetry tag designed for implantation into small, slender-bodied fishes. Detection data were collected from eight receivers placed across a coastal riverine–wetland–lake complex. Juvenile sea lamprey initiated downstream movement near nautical twilight, stopped frequently, and were more likely to move during high river discharge. Estimated survival was highest in the riverine reach, declined through the river–wetland complex, and dropped precipitously in the drowned rivermouth lake. However, the high transmission rate and resulting short battery life of the microtransmitters (as configured) likely resulted in missed detections in the lower reaches. Simulation analyses suggested survival estimation could be improved by increasing the number of tagged lamprey and staggering release locations. We offer practical recommendations for the use of this new transmitter in field studies with small anguilliform fish.
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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 | 0.003 |
| 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 | 0.000 | 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".