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Record W2960038623 · doi:10.1080/00218839.2019.1632148

<i>Nosema ceranae</i>, the most common microsporidium infecting <i>Apis mellifera</i> in the main beekeeping regions of China since at least 2005

2019· article· en· W2960038623 on OpenAlexaff
Qiang Wang, Pingli Dai, Ernesto Guzmán‐Novoa, Yanyan Wu, Chunsheng Hou, Qingyun Diao

Bibliographic record

VenueJournal of Apicultural Research · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNosema ceranaeBiologyNosemaBeekeepingMicrosporidiaSporeMicrosporidiosisHoney beeVeterinary medicineZoologyBotany

Abstract

fetched live from OpenAlex

The aim of this study was to determine the prevalence and distribution of Nosema spp. in Apis mellifera using historical worker bee samples collected between 2005 and 2010 in China. Out of 292 samples initially analysed by microscopy, 69 were Nosema spore positive. The prevalence of Nosema infections in Southern China (38.9%) was higher than in Central and Northern China (21.9 and 16.7%, respectively). Positive samples were subjected to multiplex PCR amplifications with primers corresponding to 16S rRNA specific sequences of Nosema ceranae and Nosema apis. N. apis was detected in only one sample collected in 2008 in Shandong province, whereas N. ceranae was detected in 68 samples, which indicates that N. ceranae is the most common Nosema species infecting A. mellifera in China since at least 2005.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.319
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2019
Admission routes1
Has abstractyes

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