Management Council’s Terms of Reference for the Groundfish Stock Assessment and Review
Bibliographic record
Abstract
Process for 2009-2010 (PFMC 2008). As in previous years, the Panel attempted to adhere to the spirit of the Canada-U.S. Treaty on Pacific hake / whiting, with the Panel including a member from Canada and Canadian assessment scientists providing data to the stock assessment team. The revised stock assessment and the STAR Panel Report will be forwarded to the Pacific Fishery Management Council (PFMC) and its advisory groups, and to the Canadian Department of Fisheries and Oceans (DFO) managers and the Groundfish Sub-committee of PSARC (Pacific Scientific Advice Review Committee). Both members of the stock assessment team (STAT, Drs. Owen Hamel and Ian Stewart) attended and actively participated in the meeting. Public comment was entertained throughout the three-and-a-half-day meeting, which was held at the Hotel Deca in Seattle. The STAR Panel 1 2 members were able to receive all draft assessments and supporting materials via an ftp site two weeks prior to the meeting, which was sufficient time to adequately prepare for the review of the assessment. Although data from the 2008 Canadian fishery were not incorporated into the model
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 | 0.031 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.012 | 0.007 |
| Insufficient payload (model declined to judge) | 0.068 | 0.060 |
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".