is the main culprit for the\n death and reduced populations of overwintered honey bee (
Bibliographic record
Abstract
\n The relative effect of parasite levels, bee population size, and food reserves on winter\n mortality and post winter populations of honey bee colonies was estimated. More than 400\n colonies were monitored throughout three seasons in Ontario, Canada. Most of the colonies\n were infested with varroa mites during the fall (75.7%), but only 27.9% and 6.1% tested\n positive to nosema disease and tracheal mites, respectively. Winter colony mortality was\n 27.2%, and when examined as a fraction of all morbidity factors, fall varroa mite\n infestations were the leading cause of colony mortality (associated to > 85% of\n colony deaths), followed by fall bee populations and food reserves. Varroa-infested\n colonies, with weak populations and low food reserves in the fall, significantly decreased\n spring colony populations, whereas varroa infestations and Nosema\n infections in the spring, significantly decreased bee populations by early\n summer. Overall, results suggest that varroa mites could be the main culprit for the death\n and reduced populations of overwintered honey bee colonies in northern climates.\n
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 | 0.000 |
| 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) | 0.001 | 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".