Effects of marine conditions, fishing, and smolt traits on the survival of tagged, hatchery-reared sea trout (<i>Salmo trutta trutta</i>) in the Baltic Sea
Bibliographic record
Abstract
The marine survival of tagged sea trout (Salmo trutta trutta) smolt groups (n = 236) stocked from 1970 to 2001 in the Baltic Sea was analysed using a linear mixed model. The response variable, survival rate, was associated with smolt size, release date, sea surface temperature in May, and prey fish abundance, and interactions among these factors. The effect of smolt size was in interaction with Baltic herring (Clupea harengus membras) abundance; smolt size had an optimum of about 22 cm in years when herring were abundant, but when herring were less abundant, the survival of larger smolts was higher. Early stocking in warm springs or late stocking in cold springs gave the best survival rates for trout. Changes in return activity or fishing methods have made tag returns a less reliable way of estimating survival during the last 30 years. The actual return rate of undersized fish (<40 cm) compared with their estimated proportion among captured fish decreased over time, which suggests that the survival rate for the later years was probably underestimated. It is likely that we were unable to include all the relevant explanatory variables in the model, as year effects remained significant, suggesting unknown annual variation affecting survival.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".