Bibliographic record
Abstract
This assessment applies to Pacific ocean perch (Sebastes alutus) (POP) for the US Vancouver and Columbia area combined. Catches are characterized by large removals during the mid-1960s by foreign vessels. The domestic fishery proceeded with subsequent moderate removals of between 1,000-2,000 tons per year since 1976. Catches have been further reduced by management measures to about 700 tons since 1995. In 1999 the catch was estimated at slightly higher than 500 tons and for 2000, the catches are estimated at slightly less than 300 tons. Previous assessments were done in 1992 and 1995 and involved extensive analyses of diverse data types using an age structured model (the stock synthesis program). In 1998, and in this assessment, a similar model structure was implemented. The new data presented in this assessment include updated catches, a revised length-at-age transition matrix, updated commercial length frequency data, and the 1998 NMFS triennial-trawl survey estimate of biomass and age structure. There were a number of changes in model structure from that used in the 1998 assessment. A non-informative prior was placed on steepness and a very diffuse prior was placed on the trawl survey catchability estimates reflecting the lack of relevant auxiliary information. Also the population was not assumed to be at equilibrium at the start of
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.542 | 0.456 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".