Low-frequency sounds emitted by <i>Sotalia fluviatilis guianensis</i> (Cetacea: Delphinidae) in an estuarine region in southeastern Brazil
Bibliographic record
Abstract
Recordings of the vocalizations of the dolphin Sotalia fluviatilis guianensis were made in an estuarine complex at Cananéia in southeastern Brazil over a period of 10 years (19891998). This area is characterized by mangroves and the constant presence of dolphins. Recordings were obtained at depths of 24 m using digital and analog recorders at a speed of 19 cm/s. Four classes of sounds were identified. "Whistles," which are used in social activities, occurred with the greatest frequency (χ2 = 58.92, df = 3, P < 0.001). "Calls," which were very variable in form, were the second most common class used by family groups (χ2 = 10.96, df = 2, 0.005 > P > 0.001). There were no differences in the rates at which schools emitted whistles and calls (χ2 = 2.12, df = 1, 0.25 > P > 0.10). "Gargles" were apparently emitted by calves and were similar in structure to a low-frequency call. The fourth class, "clicks," are used in echolocation. Clicks varied considerably in their frequency of occurrence and frequency of emission, and were not always detected. There were significant differences in emission rates among the four classes (χ2 = 18.73, df = 3, P < 0.001). In addition, which class of sound was emitted depended on the type of activity exhibited by the dolphins (displacement, fishing, social) and on the social structure (family or school) adopted.
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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 | 0.001 |
| 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 | 0.001 |
| 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 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".