Assessment of West of Scotland whiting (ICES Division VIa) using multiple survey data
Bibliographic record
Abstract
This paper presents an assessment of West of Scotland whiting based only on research vessel survey data. Recent ICES assessments have used data from the IBTS quarter 1 (IBTSq1) survey and commercial catch at age data, but problems with likely bias in reported catches has meant that only a limited range of years of commercial data have been included in the assessment. As a result in the assessment, values for the period 1995-2005 are dependent largely on the single survey abundance indices. By way of exploration this paper considers an assessment with all the catch data omitted to avoid possible biases resulting from misreporting but includes the four available surveys. Each survey has its weaknesses associated with design, changes in gear and vessel and yeas of missing data. However, it is perhaps useful to investigate how the surveys perform in an assessment to gauge the possible impact they have on the parameter estimates and to see how far the assessment can be taken without the use of commercial data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".