River-influenced beluga (<i>Delphinapterus leucas)</i> summer habitat use in western Hudson Bay, Canada
Bibliographic record
Abstract
River estuaries along western Hudson Bay, Canada, are important summer habitats for beluga whales ( Delphinapterus leucus (Pallas, 1776)) and subject to increasing industrial development activities including vessel traffic. The feasibility of establishing a National Marine Conservation Area (NMCA) in western Hudson Bay is under consideration, requiring baseline studies and habitat monitoring. In this study, beluga whale locations were identified using aerial photographs collected during summer 2018 of the Seal, Knife, Churchill, and Nelson River estuaries. Sentinel 2 wavelength bands were used to outline river plume boundaries for the Seal, Knife, and Churchill Rivers. Multiple discriminant analysis was used to differentiate between beluga habitat areas according to their environmental characteristics including concentration of total suspended sediments (TSS), and coloured dissolved organic matter (CDOM). The Seal River estuary, Knife River estuary, Churchill River outer estuary, Churchill River estuary, and Nelson River estuary were identified as distinct habitat areas. Resource selection functions and model selection were used to determine that habitat variables related to prey availability were important for beluga habitat selection, including TSS, CDOM, and the distance to river mouth or river plume. Identification of preferred habitat and habitat areas in this study are imperative for future management decisions including establishment of an NMCA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".