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Record W4402128041 · doi:10.1080/00218839.2024.2380425

Standard methods for European foulbrood research 2.0

2024· article· en· W4402128041 on OpenAlexaff
Giles E. Budge, Nicola Burns, Daisuke Takamatsu, Silvio Erler, Eva Forsgren, Daniela Grossar, M. Hornitzky, Meghan O. Milbrath, Hollie Pufal, Victoria Tomkies, Sarah C. Wood, Monika Yordanova, Jean‐Daniel Charrière

Bibliographic record

VenueJournal of Apicultural Research · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBiologyEuropean unionEuropean commissionBiotechnologyInternational trade

Abstract

fetched live from OpenAlex

European foulbrood (EFB) is a severe bacterial honey bee brood disease caused by the Gram-positive bacterium Melissocccus plutonius. The disease is widely distributed worldwide, and is an increasing problem in some areas. Although the causative agent of EFB was described almost a century ago, many basic aspects of its pathogenesis are still unknown. Earlier studies were hampered by insensitive and unspecific methods such as culture based techniques. Recent advances in molecular technologies have led to a boom in the methods available to study both disease and causative organism, but not all published methods offer data of equal quality, or are likely to result in success. This paper presents selected step-by-step methodologies that have been used with success in at least one laboratory of the authors and considered relevant by the consortium of authors. We hope this paper helps providing some assistance to those wishing to work on M. plutonius and EFB, and speeds up the discovery of new knowledge to improve the control of this damaging and often neglected disease.

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)0.014
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.109
Threshold uncertainty score0.365

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.017
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0130.008
Science and technology studies0.0030.003
Scholarly communication0.0050.003
Open science0.0060.004
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.1090.110

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 head0.387
GPT teacher head0.572
Teacher spread0.185 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations14
Published2024
Admission routes1
Has abstractyes

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