Putative contact calls made by humpback whales (Megaptera novaeangliae) in southeastern Alaska
Bibliographic record
Abstract
Describing the acoustic properties and usage patterns of whale vocalizations is essential for documenting their functions and biological importance. Here the authors describe the acoustic characteristics and patterns of occurrence of the most common vocalization of the humpback whale (Megaptera novaeangliae) on its southeastern Alaska summer feeding grounds; a simple frequency-modulated call referred to as the “whup”. The authors examined 59 randomly selected days of continuous data recorded from an anchored hydrophone in Glacier Bay National Park from May through September 2007-2010. Using an automated detector 1,336 whups were identified, and their physical characteristics measured. Two distinct components of each whup were measured: a low-frequency growl with a fundamental tone, and a broadband upsweep. The growl component averaged 0.47 sec duration, within a 56-187 Hz frequency range, and had a peak frequency of 94 Hz. The upsweep component averaged 0.19 sec duration over a broadband frequency range of 52-743 Hz, with a peak frequency of 93 Hz. Of the 1,336 whups identified, 61% were in multiple-call groupings. Whups were significantly more likely to occur at night than during the day (t= -2.647, df=22, p=0.0147). Due to its patterns of usage and acoustic similarity to other mysticete contact calls, the authors speculate that inter-group communication is the main function of this call.
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 | 0.001 | 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".