Short-term effects of commercial fishing on the distribution and abundance of walleye pollock (<i>Theragra chalcogramma</i>)
Bibliographic record
Abstract
Replicate acoustic surveys conducted near Kodiak Island, Alaska, USA, during summers 2001, 2004, and 2006 showed that the short-term effect of commercial fishing activities on walleye pollock ( Theragra chalcogramma ) during this period was small, in most cases too small to detect. An area with commercial fishing and a nearby comparison area where commercial fishing was prohibited were surveyed before and during the fishery. Acoustic data were used to assess changes in the abundance, geographical and vertical distributions, and small-scale spatial patterns of walleye pollock, which may have occurred after the fishery commenced. A decrease in biomass after fishing began was detected only in 2004. No changes were detected in geographical or vertical distributions that could be attributed to the fishery in any year. Adults did not appear to aggregate or disperse in response to the fishery. Juvenile aggregations did differ between the prefishery and fishery surveys in 1 of the 2 years when juveniles were present. These data suggest that changes in walleye pollock abundance and distribution caused by the fishery are likely quite small compared with natural fluctuations.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 0.000 |
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".