Survival and behaviour of migrating Atlantic salmon (Salmo salar L.) kelts in river, estuarine, and coastal habitat
Bibliographic record
Abstract
Abstract Hubley, P. B., Amiro, P. G., Gibson, A. J. F., Lacroix, G. L., and Redden, A. M. 2008. Survival and behaviour of migrating Atlantic salmon (Salmo salar L.) kelts in river, estuarine, and coastal habitat. – ICES Journal of Marine Science, 65: 1626–1634. The downstream migration of 30 Atlantic salmon (Salmo salar) kelts tagged with acoustic transmitters was monitored using 26 underwater receivers at eight locations from April to October 2006 in the LaHave River and Estuary. In all, 27 tags were detected as they left the coastal environment by the middle of May, 5 weeks after release, indicating a possible 90% kelt survival to coastal departure. Two missing tags and one dropped tag were assumed to be attributable to natural mortality in the estuary. Migration time from release to the outermost coastal receivers 24 km below the tide limit took an average of 14 d, but varied from 3 to 32 d. Some 40% of the kelts lingered and were active in the lower estuary. Five kelts monitored with depth transmitters migrated mostly at the surface in all habitats, with occasional brief descent to the bottom. A consecutive spawning salmon returned after 79 d outside the outermost array. The low rate of returns is consistent with the historical repeat spawning schedule for this river, and more precisely documents the temporal and spatial habitat use of migrating kelts.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".