WEDDELL SEAL UNDERWATER CALLING RATES DURING THE WINTER AND SPRING NEAR MAWSON STATION, ANTARCTICA
Bibliographic record
Abstract
Abstract Underwater vocalization monitoring and surveys, both on ice and underwater, were used to determine if Weddell seals (Leptonychotes weddellii) near Mawson Station, Antarctica, remain under the fast ice during winter within close range of breeding sites. Daytime and nighttime underwater calling rates were examined at seven breeding sites during austral winter and spring to identify seasonal and diel patterns. Seals rarely hauled out at any of the sites during winter, although all cohorts (adult males, females, and juveniles) were observed underwater and surfacing at breathing holes throughout winter (June–September) and spring (October–December). Seal vocalizations were recorded during each sampling session throughout the study (n= 102 daytime at seven sites collectively, and n= 5 24‐h samples at each of two sites). Mean daytime calling rate was low in mid‐winter (July) (mean = 18.9 ± 7.1 calls/min) but increased monthly, reaching a peak during the breeding season (November) (mean = 62.6 ± 15.7 calls/min). Mean nighttime calling rate was high throughout the winter and early spring (July–October) with mean nocturnal calling rate in July (mean = 61.8 ± 35.1 calls/min) nearly equal to mean daytime calling rate in November (during 24‐h daylight). Reduced vocal behavior during winter daylight periods may result from animals utilizing the limited daylight hours for nonvocal activities, possibly feeding.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".