Acoustic detection and localization of whales in bay of fundy and St. Lawrence estuary critical habitats
Why this work is in the frame
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Bibliographic record
Abstract
The detection and localization of marine mammals using passive acoustics is explored for two critical habitats in Eastern Canada.Two-dimensional hyperbolic localization is performed on time differences of arrivals o f specific calls on grids of coarsely spaced autonomous recorders and on a shore-linked coastal array o f closely spaced hydrophones.Delays are computed from cross-correlation and spectrogram cross coincidence on signals enhanced with high-frequency emphasis and noise spectral suppression techniques.The outcomes and relative performance of the two delay estimation methods are compared.The difficulties encountered under the particular conditions o f these two environments are discussed for the point o f view o f automated localisation for monitoring whales. RSUMLa dtection et la localisation de mammifres marins l'aide de l'acoustique passive est explore pour deux habitats critiques dans l'est du Canada.La technique de localisation par hyperboles en deux dimensions est utilise partir des diffrences de temps d'arrive des rseaux de systmes d'enregistrements autonomes largement espacs, ainsi qu' un rseau serr d'hydrophones relis la cte.Les dlais d'arrive sont calculs par inter-corrlation ainsi que par inter-coincidence des spectrogrammes des signaux rehausss par des techniques de rehaussement des hautes frquences et de soustraction spectrale du bruit.Les rsultats et la performance relative des deux mthodes sont compars.Les difficults rencontres dans le contexte des conditions particulires de ces deux environnements sont discutes par rapport l'automatisation de la localisation pour le monitorage des baleines.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it