A new touchscreen for behavioural research on bees
Bibliographic record
Abstract
Abstract Flying insects encounter a considerable amount of multisensorial information during their first foraging trip and need to extract and process relevant cues to efficiently navigate their environment and locate food sources. Previous studies used static stimuli to investigate visual information processing during flight and the role of floral features on detection, landing, and flower handling behaviours. However, bees come across visual information sequentially, while sampling the visual scene and presenting visual features that change after landing would allow further understanding of the chronological aspect of visual information processing. Here, we describe a new methodology that uses the ShadowSense™ Multitouch technology to present interactive floral displays where a change in visual features is triggered upon a bee's landing. Two colonies of flower naïve bumblebees ( Bombus impatiens ) were exposed to unicoloured and bicoloured unrewarded floral images in which floral guides in the form of dummy stamens were added, removed, or remained unchanged in the centre upon landing. Our findings confirm preference by flower‐naïve bumblebees for bicoloured flowers and corroborate that small central visual guides direct the place of landing. Therefore, we establish proof‐of‐concept of this new methodology for bee research by reproducing previously demonstrated behaviours and by reporting that bees react to a change in visual information on the touchscreen. To our knowledge, this is the first research providing a touchscreen technology that can reliably be used with bees. While its efficiency with similar‐sized insects is yet to be confirmed, this technology provides new approaches for research on visual information processing as well as various behaviours in insects.
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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 | 0.001 | 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 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".