An Atlantic herring (<i>Clupea harengus</i>) size selection model for experimental gill nets used in the Sound (ICES Subdivision 23)
Bibliographic record
Abstract
Size selection investigations were performed in the Sound with experimental, multipanel gill nets equipped with a broad range of mesh sizes targeting Atlantic herring (Clupea harengus). Each of the 20 experimental fishery surveys covered the central Sound from Helsingør-Helsingborg (north) to Drogden-Klagshamn (south) during the autumn, winter, and spring periods from 1993 to 1998. There was high variability in catch sizes both between and within surveys. The overall best fits, in terms of minimum total deviance across all sets, were achieved using a unimodal normal scale model. Almost all surveys showed high between-set variation, which was accounted for when estimating the mean selectivity curves using a random effects model. The selectivity curves fitted to individual sets were compared with those fitted to the combined data sets. It was demonstrated that analysing pooled data sets resulted in overdispersion and bias in the selection parameters. Irregular time series of the estimates of the selectivity parameters in the investigation period indicated negative autocorrelation with a seasonal pattern.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".