Utilisation de la surveillance acoustique passive à partir de planeurs pour la détection en temps quasi réel et la gestion dynamique des baleines noires de l'Atlantique Nord (Eubalaena glacialis) dans les zones dynamiques de navigation du chenal Laurentien
Bibliographic record
Abstract
The goal of this project was to use right whale detections made by the glider to trigger dynamic vessel management in the traffic separation scheme within Dynamic Shipping Zone C (DSZ C). A profiling glider equipped with a hydrophone system was deployed for an 89-day mission from August 16th through November 10th, 2020. The glider reported daily detections of five species of baleen whales that were validated by a trained human analyst before being distributed to Transport Canada. The glider detected right whales in DSZ C on seven survey days. In response to the glider detections, the speed limit was in place in DSZ C for 32.5 days, or 47.8 % of the survey period. On October 23rd, 2020, the glider departed DSZ C and was recovered near the west shore of Cape Breton on 12 November. The false detection rate for right whale detections at the daily scale was 0%, and the false negative rate for this species at the daily scale was 12.5%, which is within normal operating parameters for this system. The mission objectives were successfully fulfilled.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".