Managed honey bee colony losses in Canada, China, Europe, Israel and Turkey, for the winters of 2008–9 and 2009–10
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
SummaryIn 2008 the COLOSS network was formed by honey bee experts from Europe and the USA. The primary objectives set by this scientific network were to explain and to prevent large scale losses of honey bee (Apis mellifera) colonies. In June 2008 COLOSS obtained four years support from the European Union from COST and was designated as COST Action FA0803—COLOSS (Prevention of honey bee Colony Losses). To enable the comparison of loss data between participating countries, a standardized COLOSS questionnaire was developed. Using this questionnaire information on honey bee losses has been collected over two years. Survey data presented in this study were gathered in 2009 from 12 countries and in 2010 from 24 countries. Mean honey bee losses in Europe varied widely, between 7–22% over the 2008–9 winter and between 7–30% over the 2009–10 winter. An important finding is that for all countries which participated in 2008–9, winter losses in 2009–10 were found to be substantially higher. In 2009–10, winter losses in South East Europe were at such a low level that the factors causing the losses in other parts of Europe were absent, or at a level which did not affect colony survival. The five provinces of China, which were included in 2009–10, showed very low mean (4%) A. mellifera winter losses. In six Canadian provinces, mean winter losses in 2010 varied between 16–25%, losses in Nova Scotia (40%) being exceptionally high. In most countries and in both monitoring years, hobbyist beekeepers (1–50 colonies) experienced higher losses than practitioners with intermediate beekeeping operations (51–500 colonies). This relationship between scale of beekeeping and extent of losses effect was also observed in 2009–10, but was less pronounced. In Belgium, Italy, the Netherlands and Poland, 2008–9 mean winter losses for beekeepers who reported ‘disappeared’ colonies were significantly higher compared to mean winter losses of beekeepers who did not report ‘disappeared’ colonies. Mean 2008–9 winter losses for those beekeepers in the Netherlands who reported symptoms similar to “Colony Collapse Disorder” (CCD), namely: 1. no dead bees in or surrounding the hive while; 2. capped brood was present, were significantly higher than mean winter losses for those beekeepers who reported ‘disappeared’ colonies without the presence of capped brood in the empty hives. In the winter of 2009–10 in the majority of participating countries, beekeepers who reported ‘disappeared’ colonies experienced higher winter losses compared with beekeepers, who experienced winter losses but did not report ‘disappeared’ colonies.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 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 it