Testing learning as alternative to the blank slate hypothesis in the honey bee, Apis mellifera
Bibliographic record
Abstract
Reliable recognition of nestmates and discrimination against non-nestmates is key to the integrity of social insect colonies. Cuticular hydrocarbon profiles play a key role in this recognition process in many species, including honey bees. Newly emerged worker bees are largely devoid of cuticular hydrocarbons and therefore believed to represent a "blank slate" that is not discriminated against and instead accepted into other colonies regardless of colony origin. However, instead of being unrecognizable, the absence of cuticular hydrocarbons may also represent a recognizable "Gestalt". Thus, an alternative hypothesis for the universal acceptance of newly emerged workers may be that older workers in every colony learn the absence of cuticular hydrocarbons as a familiar stimulus that belongs to their colony because other such workers are constantly emerging under normal circumstances. Here, we tested this hypothesis by comparing the response to newly emerged workers between bees that matured in colonies with and without newly emerging bees. Contrary to our prediction, we found no significant difference between these two experimental groups in an aggression bioassay towards newly emerged workers. We thus failed to provide empirical evidence against the blank slate hypothesis. However, the groups displayed significant differences in aggression towards foragers from their own respective colonies, indicating that the emergence of new workers in a colony can affect group discriminatory behavior in honey bees. Furthermore, we identified a negative effect of temperature on aggressive behavior toward newly emerged workers.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".