Combining bottom trawls and acoustics in a diverse semipelagic environment: What is the contribution of walleye pollock (<i>Gadus chalcogrammus</i>) to near-bottom acoustic backscatter in the eastern Bering Sea?
Bibliographic record
Abstract
The abundance of walleye pollock (Gadus chalcogrammus) in the eastern Bering Sea is estimated in part through fisheries-independent acoustic trawl (AT) surveys, which currently use acoustic backscatter data down to 3 m above the bottom. A large portion of adult pollock are demersal, and these estimates will become more accurate if the survey is extended closer to bottom. The purpose of this project was to assess the feasibility of extending the AT survey closer to the bottom by estimating the contributions of each demersal fish species to observed acoustic backscatter in the highly diverse near-bottom region. This was accomplished by fitting a regression model to simultaneously collected acoustic backscatter and bottom trawl catch data. Pollock were the dominant source of acoustic backscatter among demersal species, accounting for 85.9% ± 4.8% of acoustic backscatter (mean ± standard deviation). A method was developed to extend the AT survey to within 0.5 m of the bottom, and when applied to the 1994–2014 surveys, pollock biomass increased by a mean of 28% ± 9%.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".