Inter-benchmark Protocol on Sole (Solea solea) in divisions 7.f and 7.g (Bristol Channel, Celtic Sea) (IBPBRISOL 2019)
Bibliographic record
Abstract
The Inter-benchmark Protocol on Sole (Solea solea) in divisions 7.f and 7.g (Bristol Channel, Celtic Sea (IBPBrisol) met by correspondence during four skype meetings, chaired by Noel Cadigan (Centre for Fisheries Ecosystems Research (CFER), Fisheries and Marine Institute of Memorial University of Newfoundland, Canada) and attended by invited external expert John Wiedenmann (Department of Ecology, Evolution and Natural Resources, Rutgers University, New Jersey, USA). The focus of this inter-benchmark was to improve the quality of the tuning series that are included in the current assessment. ToRs on the UK CBT tuning fleet and additional survey information were postponed to the upcoming benchmark in 2020.A new Belgian commercial tuning index was constructed focusing on the landings and effort data of pure trips from the large fleet segment of the Belgian beam trawl fleet fishing in divisions 7.f and 7.g. Several models were tested and a GLMM including a categorical year effect, a log-linear relationship between the engine power of a beam trawler and the landing rate, a categorical temporal effect ‘month’ and a categorical spatial effect ‘ICES statistical rectangle’ were retained. Also, a variable dispersion factor was added, including ‘month’ and ‘ICES statistical rectangle’. This tuning fleet provides information from 2006–2017 and focusses on ages 2–9 with a good internal consistency.Several XSA assessment runs were trialed at the inter-benchmark. The final run included the new Belgian CBT series from 2006–2017 (ages 2–9), the original Belgian CBT series from 1971–1996 (ages 3–9), the UK CBT from 1991–2012 (ages 3–8) and the UK BTS Q3. This resulted in an increase of the SSB and a decrease of F in recent years.New reference points were estimated. FMSY analyses were conducted with Eqsim.Future research and data requirements were identified, also by the external reviewers.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.018 |
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".