Microhabitat Use and Vertical Habitat Partitioning of Juvenile Atlantic(Gadus morhua) and Greenland (Gadus ogac) Cod in Coastal Newfoundland
Bibliographic record
Abstract
Twenty co-occurring juvenile gadids (10 Gadus ogac and 10 Gadus morhua) were surgically implanted with ultrasonic transmitters with depth sensors and continuously monitored for up to 23 days in the summers of 2009 and 2010 to test fine-scale habitat use and vertical distribution overlap in coastal Newfoundland (>18700 positional fixes). A habitat map with 8 substrate and 3 slope classes (low (<5°), moderate (5-10°), and high (>10°)) was generated from acoustic data and coincident video data using seabed mapping software (QTC). Fish locations were integrated with a habitat map to assess and quantify habitat preference. Both species avoided fine gravel/sand substrates with little vegetation and selected for large particle (cobble and boulder) substrates with moderate or dense vegetation, and spent the majority of time in < 10 m of water. Nevertheless, species differences in habitat use were evident. G. ogac typically remained in close proximity to the seafloor whereas G. morhua was often distributed more pelagically and showed greater variation in vertical distribution. Habitat use and vertical distribution patterns were consistent across the diel period. Our results suggest that despite high overlap in habitat use, G. morhua and G. ogac often segregate vertically in the water column, which may reduce competitive interference. We suggest that these patterns are related to differences in diet.
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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 | 0.000 | 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".