Towards a balanced presentation and objective interpretation of acoustic and trawl survey data, with specific reference to the eastern Scotian Shelf
Bibliographic record
Abstract
A debate has developed over the ecosystem consequences following the collapse of Atlantic cod throughout the coastal waters of eastern Canada. The explosive increase in pelagic fish abundance in scientific bottom-trawl catches on the eastern Scotian Shelf has been interpreted as being due to either (i) a “pelagic outburst” of forage fish abundance resulting from predator release or conversely (ii) a change in pelagic fish vertical distribution leading to a “suprabenthic habitat occupation” thereby increasing their availability to bottom trawls. These two interpretations have diametrically opposing ecological consequences and suggest different management strategies for these important forage fish species. We argue that an objective evaluation of the available evidence supports the hypothesis that the abundance of forage fish has not increased in response to the demise of cod and other top predators, and the reliance on a single sampling gear with low catchability has biased and will continue to bias the interpretation of demographic trends of pelagic fish populations. We advocate that multiple sampling technologies providing alternative perspectives are needed for the monitoring and management of the various trophic levels if we are to achieve a balanced and objective understanding of marine ecosystems.
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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 | 0.144 | 0.215 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.020 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".