Megafauna survey in Acorez : perspectives with Bombyx Sonobuoy
Bibliographic record
Abstract
Monitoring soundscapes provides data for several purposes, such as research and management. Marine megafauna, especially cetaceans, have been monitored at the Azores archipelago using the BOMBYX system, composed of 4 hydrophones. Besides recording biological sounds, anthropogenic noise was also recorded, due to the close location of shipping routes at SE of São Jorge island.There are 28 species of cetaceans seen in the region, but the most frequent and more expected to be recorded are: Sperm whale, Bottlenose dolphins, Risso's dolphins, Common dolphins, Striped dolphins, Spotted dolphins, Blue whales, Fin whales, Sei whales, Humpback whales, Short-finned pilot whales, False killer whales, Cuvier's beaked whale, Mesoplodon densirostris, Mesoplodon bidens, Northern Bottlenose whales. There could also be records of Bryde's whale, Minke whale, Mesoplodon europaeus, Mesoplodon mirus, Pygmy sperm whale, Dwarf sperm whale.The BOMBYX EUROPAM sonobuoy is equipped with real time transmission and powered by solar panels. With a small size, only 1m high, it supports a 1 m diameter acoustic antenna, that allows to diarize the different sources, anthropic and biophonic, in azimuth and elevation. It aims to monitor the interactions of the megafauna against anthropic pressure. It includes a real time species identification, and can thus alert on some risk of collision. We will present the overview of the Bombyx Surveys
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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 | 0.001 |
| 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) | 0.002 | 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".