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Record W3184055019

Impacts of tracheal mites (Acarapis woodi (Rennie)) on the respiration and thermoregulation of overwintering honey bees in a temperate climate

2000· dissertation· en· W3184055019 on OpenAlexfundno aff
Alison Skinner

Bibliographic record

VenueThe Atrium (University of Guelph) · 2000
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaAgricultural Adaptation Council
KeywordsOverwinteringThermoregulationTemperate climateHoney BeesEcologyRespirationBiologyGeographyBotany
DOInot available

Abstract

fetched live from OpenAlex

The impact of the tracheal mite ('Acarapis woodi') on the respiration and thermoregulation of wintering of honey bees was investigated. The oxygen consumption rate (mlO2/bee/hr) of individual bees infested with mites (8.93 ± 0.07) was significantly lower than for non-infested bees (9.82 ± 0.07) after acclimatizing to 15°C. Bees with sealed spiracles had the lowest oxygen consumption rate (8.33 ± 0.09). The oxygen consumption rate after acclimatization to 24°C and to 5°C was significantly lower for clusters (200 bees) of tracheal mite infested bees than for non-infested bees. Colonies with high tracheal mite prevalence had significantly lower core cluster temperatures in comparison to colonies with low mite prevalence. As an extension of this research, protection and means of mite control were investigated. For winter protection of bee colonies, the indoor wintering facility and the Davies system offered more protection than did the waxed cardboard boxes and the tar paper wrap. A spring application of formic acid reduced tracheal mite infestation by 93%. Microencapsulated menthol reduced mite infestation by 50%. Lowering tracheal mite prevalence prior to winter and providing an efficient wintering system did reduce the negative effects that tracheal mites have on the oxygen consumption rates of honey bees thus improving their thermoregulatory ability and their survivorship.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.982
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.238
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2000
Admission routes1
Has abstractyes

Explore more

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