Distribution of Greenland Halibut and By-catch Species that Overlap the 200-mile Limit Spatially and in Relation to Depth – Effect of Depth Restrictions in the Fishery. Distribution of the Fishable Biomass of the Main Commercial Species of Fish in Relation to Depth
Bibliographic record
Abstract
It is thought that measures currently in operation in the NAFO Regulatory Area are not adequate for the protection\nof the juvenile fish. The largest fishery in the NRA and thus the one of greatest concern is that directing for\nGreenland halibut. As well, the need to reduce by-catch of any species in the Greenland halibut and other fisheries\nhas been noted. Because of the range of depths currently fished, the Greenland halibut fishery not only focuses on\nthe juvenile component of the population but also takes significant by-catch. This paper is a compendium of 12\npapers presented recently to Scientific Council. Information on the distribution of Greenland halibut including\ndistribution of undersized (below 35 cm, the Canadian minimum landing size) and mature and immature components of\nthe population based on both survey and commercial information is presented. The paper also elaborates on the\ndistribution of other commercial species that occur in the NRA, those that may be taken as by-catch in the directed\nGreenland halibut or other NRA fisheries, including those that overlap the Southeast Shoal.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".