Colony‐level chemical profiles do not provide reliable information about colony size in the honey bee
Bibliographic record
Abstract
1. Chemical communication facilitates colony function across social insects, providing workers with information about individual and colony state. Although workers use chemical cues to detect developmental transitions in individuals, it is unknown whether workers can also use colony‐level chemical profiles to detect the developmental state of their colony. Indeed, it is largely unknown how colony‐level chemical profiles change as colonies grow and develop. 2. Reproductive onset is a major developmental transition and, in the honey bee, Apis mellifera , colonies must surpass a threshold colony size before workers will invest in reproduction. Given the ubiquity of chemical communication, the present study investigated whether colony‐level chemical profiles change with colony size. 3. Chemical compounds deposited by workers of three colony sizes (5000, 10 000, 15 000 workers) collected over a 4‐day time‐series (0, 12, 24, 48, 72, and 96 h), as well as worker cuticular lipids, were sampled. 4. In total, 26 compounds deposited on nest surfaces and 20 compounds in worker cuticular lipids were identified; it took up to 24 h for sampled nest surfaces to reach saturation in the number and amount of deposited compounds. 5. Among these compounds, no qualitative or quantitative indicators of colony size were found, suggesting that deposited chemical compounds are not semiochemicals in this context. Volatile pheromones have also been shown previously to not play a role in signaling colony size. Therefore, honey bee workers are unlikely to use deposited chemical cues to detect colony size, and must rely instead on other modalities, such as physical cues of worker density.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".