The ‘‘gunshot’’ sound produced by male North Atlantic right whales and its potential function in reproductive advertisement
Bibliographic record
Abstract
North Atlantic right whales (Eubalaena glacialis) commonly use sound to mediate social interactions between individuals. Surface active groups (SAGs) are the most commonly observed social interaction on the summer feeding grounds. These groups are typically composed of an adult female with two or more males engaged in social behavior at the surface. Several distinct types of sounds have been recorded from these groups. One sound commonly recorded from these groups is a brief broadband sound, referred to as a gunshot sound because it sounds like a rifle being fired. This sound has been recorded in the Bay of Fundy, Canada from both lone whales (N=9) and social SAGs (N=49). Those lone whales producing gunshot sounds whose sex could be determined (N=9) were all mature males. In surface active groups, the rate of production of gunshot sounds was weakly correlated with the total number of males present in the group. Given the behavioral contexts of gunshot sound production by male whales, gunshots probably function in a reproductive context as an agonistic signal directed toward other males, an advertisement signal to attract females, or a combination of the two functions.
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 | 0.000 | 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) | 0.001 | 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".