Characterizing the Variability of a Physical Driver of North Atlantic Right Whale Foraging Habitat Using Altimetric Indices
Bibliographic record
Abstract
Physical ocean circulation features, especially the Gaspé Current (GC) intrusion, influence the transport and aggregation of whale prey, thereby influencing the whale foraging habitat in the Gulf of St. Lawrence (GSL), Canada. We employ satellite altimetry-derived sea level anomaly (SLA) indices to monitor interannual variations in the intensity of the GC in the North Atlantic Right Whale (Eubalaena glacialis; NARW) habitat in the GSL. Measurements of surface slope and volume transport are taken from the SLA profiles along a repeating ground track of the Jason-2/3 satellites. These are employed as complementary proxies in characterizations of physical processes in the GSL. The relationship between altimetric indices and indices of zooplankton abundance are explored in the southern GSL. Results demonstrate that an altimetric index estimated from surface slope (Indexslope−half) is correlated with river discharge of the St. Lawrence River and can be utilized to infer variations in GC intensities. Time series of the altimetric indices during 2009–2021 are found to exhibit interannual and seasonal environmental variability, which influence transport into the southern GSL. As captured by the altimetric indices, these features of the surface ocean circulation can be linked to zooplankton variations in the Shediac Valley, where NARWs are frequently observed. Therefore, in linking physical drivers of ocean dynamics to the NARW foraging habitat, variations in these indices can also potentially help describe some features of the distribution patterns of NARW sightings in this area.
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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 | 0.001 |
| 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) | 0.000 | 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".