Long-term trends in the honeybee ‘whooping signal’ revealed by automated detection
Bibliographic record
Abstract
It is known that honeybees use vibrational communication pathways to transfer information. One honeybee signal that has been previously investigated is the short vibrational pulse named the 'stop signal', because its inhibitory effect is generally the most accepted interpretation. The present study demonstrates long term (over 9 months) automated in-situ non-invasive monitoring of a honeybee vibrational pulse with the same characteristics of what has previously been described as a stop signal using ultra-sensitive accelerometers embedded in the honeycomb located at the heart of honeybee colonies. We show that the signal is very common and highly repeatable, occurring mainly at night with a distinct decrease in instances towards midday, and that it can be elicited en masse from bees following the gentle shaking or knocking of their hive with distinct evidence of habituation. The results of our study suggest that this vibrational pulse is generated under many different circumstances, thereby unifying previous publication's conflicting definitions, and we demonstrate that this pulse can be generated in response to a surprise stimulus. This work suggests that, using an artificial stimulus and monitoring the changes in the features of this signal could provide a sensitive tool to assess colony status.
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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 | 0.000 | 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 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".