Influence of origin on migration and survival of Atlantic salmon (Salmo salar) in the Bay of Fundy, Canada
Bibliographic record
Abstract
Atlantic salmon ( Salmo salar ) smolts of wild and hatchery origins (n = 522) were tagged with ultrasonic transmitters and monitored at successive arrays of submerged receivers during migration from five watersheds in three regions of the Bay of Fundy (BoF), Canada. Two of the regions had endangered inner BoF salmon populations. Migration success of postsmolts leaving the BoF varied widely among 13 groups monitored (3%−70%) and was influenced by behaviour and passage time. Region of origin was the key variable in habitat-specific survival models selected using the Akaike information criterion. Rearing origin, migration and release timing, and smolt size were important variables in some habitats. Estimated survival rates (overall and habitat specific) differed markedly among salmon populations of different regions. Mediocre estuarine survival of smolts (0.54) from the outer BoF region affected overall survival (0.66). Poor survival (0.21) in coastal areas of the distant inner BoF region and mediocre survival in other habitats resulted in low overall survival (0.06) that severely limited the potential for population recovery. Potential predators were abundant in habitats where survival was lowest. High survival of salmon from the intermediate inner BoF region in all habitats (0.81–0.93) was not responsible for their failure to return.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".