In-air and underwater sounds of hooded seals during the breeding season in the Gulf of St. Lawrence
Bibliographic record
Abstract
The hooded seal is a migratory species inhabiting the North Atlantic. Passive acoustic monitoring (PAM) conducted over spatial scales consistent with their known and potential habitat could provide insight into seasonal and spatial occurrence patterns of this species. Hooded seal airborne and underwater acoustic signals were recorded during the breeding season on the pack ice in the Gulf of St. Lawrence in March 2018 to better characterize their acoustic repertoire (notably underwater calls). In-air and underwater signals were classified into 12 and 22 types, respectively. Signals produced by males through the inflation and deflation of the proboscis and septum were the predominant sounds heard on the ice surface. Five of the 22 underwater signals were proboscis and septum noises. The remaining underwater signals (17) were categorized as voiced calls and further analyzed using two classification methods. Agreement with the initial subjective classification of voiced calls was high (77% for classification tree analysis and 88% for random forest analysis), showing that 12-13 call types separated well. The hooded seal's underwater acoustic repertoire is larger and more diverse than has been previously described. This study provides important baseline information necessary to monitor hooded seals using PAM.
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 | 0.000 |
| 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) | 0.001 | 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".