Deep-ocean predation by a high Arctic cetacean
Bibliographic record
Abstract
Abstract A bioenergetic model for two narwhal (Monodon monoceros) sub-populations was developed to quantify daily gross energy requirements and estimate the biomass of Greenland halibut (Reinhardtius hippoglossoides) needed to sustain the sub-populations for their 5-month stay on wintering grounds in Baffin Bay. Whales in two separate wintering grounds were estimated to require 700 tonnes (s.e. 300) and 90 tonnes (s.e. 40) of Greenland halibut per day, assuming a diet of 50% Greenland halibut. Mean densities and length distributions of Greenland halibut inside and outside of the narwhal wintering grounds were correlated with predicted whale predation levels based on diving behavior. The difference in Greenland halibut biomass between an area with high predation and a comparable area without whales, approximately 19 000 tonnes, corresponded well with the predicted biomass removed by the narwhal sub-population on a diet of 50–75% Greenland halibut.
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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 | 0.001 | 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".