Visual choice behavior by bumblebees (Bombus impatiens) confirms unsupervised neural network’s predictions.
Bibliographic record
Abstract
The behavioral experiment herein tests the computational load hypothesis generated by an unsupervised neural network to examine bumblebee (Bombus impatiens) behavior at 2 visual properties: spatial frequency and symmetry. Untrained "flower-naïve" bumblebees were hypothesized to prefer symmetry only when the spatial frequency of artificial flowers is high and therefore places great information-processing demands on the bumblebees' visual system. Bumblebee choice behavior was recorded using high-definition motion-sensitive camcorders. The results support the computational model's prediction: 1-axis symmetry influenced bumblebees' preference behavior at low and high spatial frequency patterns. Additionally, increasing the level of symmetry from 1 axis to 4 axes amplified preference toward the symmetric patterns of both low and high spatial frequency patterns. The results are discussed in the context of the artificial neural network model and other hypotheses generated from the behavioral literature.
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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".