Using passive sonic telemetry methods to evaluate dispersal and subsequent movements of hatchery-reared white sturgeon in the Kootenay River
Bibliographic record
Abstract
A total of 35, age 1 juvenile Kootenay River white sturgeon (Acipenser transmontanus), were fitted with sonic tags in 2005 and released as part of larger hatchery release groups at five sites to evaluate dispersal and subsequent movements (seven tags per site). Juvenile sturgeon released at three locations within the deep, low gradient reach (typical gradient of 0.02 m km−1 and velocities of <0.4 m s−1) of the Kootenay River below Bonners Ferry, ID showed substantial dispersal both up and downstream; however, downstream redistribution was more common. White sturgeon from all three release locations overlapped during dispersal, with 9% of tagged fish moving from river release sites into Kootenay Lake. The three hatchery release locations in this low gradient reach produced good dispersal of hatchery progeny into available habitats. Tagged fish released above Bonners Ferry in the shallow, higher gradient reach (typical gradient of 0.6 m km−1, and velocities >0.8 m s−1) at two additional sites all moved downstream of the gradient break at Bonners Ferry, ID into the lower gradient reach within 2 months of release. In total, 93% of these tagged fish relocated to the low gradient section within 25 days of release, with some fish undertaking this movement within 1 day. In general, age 1 hatchery release juveniles were mobile and capable of substantial movements.
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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 | 0.001 | 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".