Do habitat measurements in the vicinity of Atlantic salmon (<i>Salmo salar</i>) parr matter?
Bibliographic record
Abstract
Abstract Atlantic salmon, Salmo salar L., parr habitat characterisation is usually performed by in situ measures of key environmental variables taken at the exact fish location if the fishing gear allows precise pinpointing of this location, or in large sampling sections covering a river reach or mesohabitat, often ignoring variability in the immediate vicinity around individual fish. These data may be critically important in the development and validation of habitat preference models. The influences of seven increasing distances of measures, the variation of the number of considered measures and the depth of velocity measurement (bottom or 0.6 of the depth) in the calculations of HSI (Habitat Suitability Index) from a multiple‐experts fuzzy model of Atlantic salmon parr habitat were tested. When a parr was present, six measures collected in a 50‐cm radius around the fish to provide an average measure as input data and velocity measured at 60% of the depth gave the highest HSI values. These results show some potential for the use of an intermediate study scale, between micro‐ and mesohabitat, and questions how fish habitat conditions are currently measured.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".