The low-frequency vocal repertoire of adult African dwarf crocodiles
Bibliographic record
Abstract
Acoustic techniques are rapidly becoming powerful tools for species monitoring and biodiversity assessment. These methods can be particularly appropriate for forest-dwelling crocodiles which are difficult to survey visually. However, basic vocal-repertoire data is lacking for many of the poorly known species. Here, we used passive acoustic recorders to capture 97 spontaneous vocal signals from a pair of captive adult African dwarf crocodiles (Osteolaemus tetraspis). We catalogued their acoustic repertoire and compared the calls recorded in captivity with 201 suspected wild O. tetraspis calls recorded in Gabon to determine whether the wild calls belonged to the same species. Captive and wild crocodiles produced the same four types of calls, not previously identified in other crocodylids. Short, low-frequency “drums” (31±12 Hz), longer, low-frequency “rumbles” (40 ± 14 Hz), as well as higher frequency “moos” (299 ± 133 Hz) and “gusts” (219 ± 108 Hz). Our results provide reference for species identification and support implementation of acoustic-based methods for African dwarf crocodile monitoring and conservation assessment. The data can further contribute to landscape-wide biodiversity monitoring and counter-poaching activities, as well as improving our understanding of crocodilian ecology and behaviour.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".