Report of the NAFO Joint Commission-Scientific Council Working Group on Ecosystem Approach Framework to Fisheries Management (WG-EAFFM) Meeting
Bibliographic record
Abstract
1. Opening by the co-Chairs, Robert Day (Canada) and Andrew Kenny (EU) \n2. Appointment of Rapporteur \n3. Adoption of Agenda \n4. SC response to FC requests for advice: \na. Consideration of 2014 SC advice regarding extent of the New England and Corner Rise Seamounts (Annex 13 of FC Doc. 16-20) \nb. Risk assessment of scientific surveys impact on VME in closed areas (2016 FC Request to SC #3) \n5. Discussion of ongoing matters: \na. Assessment of NAFO bottom fisheries SAI (2016 FC Request to SC # 6) \nb. Progress of analysis undertaken by EU NEREIDA funded research project \nc. Update on identification and mapping of sensitive species and habitats in the NAFO area \nd. Further development and application of the Ecosystems Approach to Fisheries (EAF) Roadmap, including further consideration of any issues raised at the Scientific Council Meeting, 01-15 June 2017 \ne. Alfonsino fishery on seamounts in the NAFO Regulatory Area. \n6. Recommendations to forward to the Commission and Scientific Council \n7. Other Matters \na. Presentation: Canada’s Marine Conservation targets for 2017 and 2020: The Role of Fisheries \nb. NAFO Working Group on Improving Efficiency of NAFO Working Group Process \nc. Recommendation for a new co-Chair \nd. Timely availability of meeting reports \n8. Adoption of Report \n9. Adjournment
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.045 | 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".