Comparative bioacoustical studies on flight and buzzing of neotropical bees
Bibliographic record
Abstract
The presence of bees is typically accompanied by the humming sound of their flight. Bees of several tribes are also capable of pollen collecting by vibration, known as buzzing behaviour, which produces a buzzing sound, different from the flight sound. An open question is whether bee species have species-specific buzzing patterns or frequencies dependent of the bees' morphology or are capable to adjust their indivudual buzzing sound to optimize pollen return. The investigations to approach this issue were performed in northeastern Brazil near Recife in the state of Pernambuco. We present a new field method using a commercially available portable system able to record the sound of bees during flight and buzzing at flowers. Further, we describe computer linguistical algorithms to analyse the frequency of the recorded sound sequences. With this method, we recorded the flight and buzzing sequences of 59 individual bees out of 12 species visiting the flowers of Solanum stramoniifolium and S. paniculatum. Our findings demonstrate a typical frequency range for the sounds produced by the bees of a species. Our statistical analysis shows a strong correlation of bee size and flight frequency and demonstrate that bee species use different frequency patterns.
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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 | 0.000 |
| 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".