Science response: groundfish data update 2021
Bibliographic record
Abstract
The combination of fshery-dependent data, such as catch and effort, and fshery-independent survey data, such as biomass indices and age compositions, form the backbone of most fsheries stock assessments. Fisheries and Oceans Canada (DFO) manages vast quantities of such data on groundfsh species in British Columbia (BC). However, formal stock assessments are not conducted on an annual basis for most stocks, and so much of these data are not summarized to represent the nature of the data holdings. The groundfsh data synopsis report was developed to provide a snapshot of long-term and recent population and fshing trends, as well as data availability, for all major BC groundfsh species of commercial and conservation interest (Anderson et al. 2019, Anderson et al. 2020). The report was published as a Canadian Science Advisory Secretariat (CSAS) Research Document (Anderson et al. 2019) to facilitate review of the methods, with the intent to update the report on a regular schedule. The usefulness of the report depends on its data remaining up-to-date. Since the initial 2019 report, three new years of survey and commercial data have become available, as well as updated stock assessment Research Documents, Science Advisory Reports, and Science Responses. DFO Science Branch has requested an update to the groundfsh data synopsis report including all commercial and survey data available up to the end of 2021. The advice arising from this CSAS Science Response will provide an overview of available groundfsh data and fshing and population trends to inform DFO Science and Fisheries Management staff in stock monitoring and prioritization. This update applies the previously peer-reviewed approach to generate up-to date fgures representing data such as biomass indices, commercial catch, species distribution, and age and length composition data for the 113 species. This Science Response results from the Science Response Process of March 29, 2022 on A data synopsis for British Columbia groundfsh: 2021 update.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.108 | 0.097 |
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".