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Record W4223536824 · doi:10.1128/spectrum.02769-21

Droplet Digital PCR-Based Detection and Quantification of GyrA Thr-86-Ile Mutation Based Fluoroquinolone-Resistant Campylobacter jejuni

2022· article· en· W4223536824 on OpenAlexaff
Yi Luo, Wenting Zhang, Yiluo Cheng, Qin Lu, Yunqing Guo, Guoyuan Wen, Huabin Shao, Zhenyu Cheng, Qingping Luo, Téngfēi Zhāng

Bibliographic record

VenueMicrobiology Spectrum · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsDalhousie University
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsCampylobacter jejuniMutantBiologyMicrobiologyDigital polymerase chain reactionWild typeSanger sequencingDNA gyraseMutationPolymerase chain reactionGeneticsEscherichia coliBacteriaGene

Abstract

fetched live from OpenAlex

Campylobacter jejuni is considered to be the leading cause of human bacterial gastroenteritis worldwide, and fluoroquinolones (FQs) are the main choices for the treatment of bacterial gastroenteritis in clinical practice. In theory, antimicrobial susceptibility testing should help us to choose the most appropriate drugs for the treatment.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.684

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)0.0010.000

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 head0.014
GPT teacher head0.200
Teacher spread0.187 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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