The distribution of <scp>subarctic</scp> and boreal deep‐sea demersal fish assemblages across environmental gradients of the northwest Atlantic
Bibliographic record
Abstract
The oceanography of the Labrador Sea is well studied because of its globally important deep-water convection that oxygenates the deep ocean and drives climate-regulating ocean currents. However, little is known about the fish communities that inhabit this area, particularly beyond the depths accessible to standard research surveys and commercial fishing activities. We used baited longline surveys to characterize important components of demersal fish communities across a depth gradient of 200-3000 m and compared these data to a similar dataset collected c. 1200 km to the south in the Flemish Cap Region. We found demersal fish communities in the Labrador Sea to be similar to those of the Flemish Cap Region despite unique oceanography and lower primary productivity in the Labrador Sea. Moreover, both areas had high abundance, biomass, and species richness at intermediate depths that suggests factors beyond depth drive community structure in the deep ocean. These data are important for identifying high-value areas for potential protective measures in the northwest Atlantic and provide necessary data with which to assess potential environmental impacts of extractive industries that are expanding north and to deeper waters.
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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 | 0.001 |
| 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".