Results of follow-up experiments to “Odorant cues linked to social immunity induce lateralized antennal stimulation in honey bees ( <i>Apis mellifera</i> L.)”
Bibliographic record
Abstract
Abstract In 2017, we published the paper “Odorant cues linked to social immunity induce lateralized antennal stimulation in honey bees ( Apis mellifera L.)” in Scientific Reports . Since then, we have performed three follow-up experiments which have either negative or contradictory results. Previously, we used electrophysiology to show that hygienic bees displayed significantly higher sensitivity to β-ocimene when stimulated via their left antennae compared to their right. We repeated this assay using worker honey bees from a single hygienic colony and found, to our surprise, that the right antennae elicited higher sensitivity. We also previously attempted to identify a molecular basis for lateralization by using mass spectrometry-based proteomics to compare left and right antennal proteomes. Of the 1,845 proteins, none were differentially expressed. Here, we repeated this experiment but employed orthogonal peptide fractionation to increase proteome coverage to 3,114 proteins; however, still none were differentially expressed. Finally, we attempted to manipulate gene expression of a key antennal odorant binding protein linked to hygienic behaviour (OBP18) using RNA interference via antenna microinjection. We were not able to achieve long-lasting OBP18 knock-down, but comparing the proteomes of untreated, mock dsRNA-treated and OBP18 dsRNA-treated worker antennae revealed numerous off-target effects of the act of injecting alone. By openly reporting this data, we hope to set an example for information transparency.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".