Editorial: Applied bee science and technology transfer
Bibliographic record
Abstract
Honey bees (Apis mellifera L) are essential contributors to food production as main pollinators in 18 agricultural ecosystems. However, beekeeping faces many challenges related to a variety of stressors 19 that affect the survivorship of honey bee colonies and compromise their productivity. For example, 20 the parasitism caused by Varroa destructor is linked to colony losses and low honey production. The 21 adaptability that varroa mites have demonstrated to different environments out of their original range 22and their capacity to cause disease and vector virulent viruses is of extreme concern. Efforts to 23 understand the biology of the parasite, its relationship to viruses, and the discovery of novel methods 24 to control its population growth have been instrumental in supporting the beekeeping industry. and hygienic behaviours and found dysregulation of some genes in bee's heads and bodies, 60advancing the understanding of molecular mechanisms behind varroa resistance and the possible 61 implementation of biomarkers in selective breeding. 62Part of an IPM strategy for varroa mite control is the use of organic acaricides, like oxalic acid. 63Tellarini Prieto et al. addressed one key question that beekeepers using oxalic acid vapour have: the 64 product's toxicity. Although the authors reported a temporary increase in adult bee mortality, they 65 found no effects on colony or queen health when using 20 g of oxalic acid. The study could have 66 implications for label recommendations and the effective use of oxalic acid vapor for varroa control. 67Additionally, Killiam et al. explored the role of honey bee gut microbiota in promoting honey bee 68 health. Specifically, they reviewed and hypothesized how supplementation of food with lactic acid 69 bacteria could influence social behaviours, enhancing hive health or performance. 70Lastly, laboratory research has led to potential treatments for various diseases that affect honey bees, 71 including varroa mites, but their application at the hive level is challenging for many reasons, such as 72 the effective distribution of therapeutic agents within the colony. Tropilaelaps mites. The use of new technologies and innovative science can greatly increase bee 83 health and improve honey bee productivity, which will benefit agricultural systems. We are grateful 84 to the authors who contributed to this research topic, the reviewers, and the editorial team.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".