Floral Categorization by Bumblebees: The Perceptual and the Functional
Bibliographic record
Abstract
This study examines generalization and perceptual similarity judgments in bumblebees (Bombus impatiens) and addresses whether category formation of floral stimuli is based upon perceptual floral features alone or foraging experiences from reward associations. Previous experiments have found that bees transfer learning based on category membership, but little is known as to how membership is formed. Two experiments using twelve bumblebee colonies examined a) if bees were able to generalize between flowers with little or no perceptual similarity, and b) if bees were able to change which features of the flowers they generalize under different circumstances. All bees were given discrimination training in a radial arm maze using objects and corresponding photographs. Bees in Experiment 1 were trained to categorize stimuli based upon their reward associations while ignoring their perceptual features. Bees in Experiment 2 were trained to categorize either by floral type or dimensionality (2D vs 3D) of the stimuli. Results of tests using unrewarding stimuli revealed that bees were unable to group items without perceptual similarity cues. When perceptually similar flowers did not share the same reward, bees still generalized between them, regardless of experience. However, the reward values of the flowers were not spontaneously disregarded by the bees. Generalizations differed based on the bee’s experiences, although preferences for perceptual similarity remained. Bees grouped flowers based on the relevant features learned through experience rather than just relying on perceptual similarity, but also do not immediately discount similar flowers during foraging, giving a preliminary insight into the role of function in perceptual similarity judgments.
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 | 0.001 | 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) | 0.000 | 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".