Age-specific shifts in Greenland halibut (Reinhardtius hippoglossoides) distribution in response to changing ocean climate
Bibliographic record
Abstract
Abstract Fish distribution is strongly influenced by temperature, with populations predicted to respond to ongoing changes in ocean climate by adapting distribution to maintain preferred thermal habitats. Over the last several decades, the Northwest Atlantic off Newfoundland, Canada has experienced wide variation in temperature and significant changes in the structure of the marine community. A period of particularly cold ocean conditions from the mid-1980s to mid-1990s saw Greenland halibut occupying deeper waters, and moving farther offshore and southward. Distributional shifts across periods of varying thermal conditions were most pronounced in the youngest ages. While no specific nursery areas were evident, these young fish typically occurred in shallower waters where temperatures were more variable, moving deeper with age. Sensitivity to changing ocean climate may vary with age. This adaptation to shifting temperatures suggests that this species is likely to alter its distribution in the face of continued changes in ocean climate. Age-specific differences in response to changing temperature have potential implications for ecosystem interactions and fisheries management.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".