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Record W2163779088 · doi:10.1139/w11-022

Validation and standardization of IS900 and F57 real-time quantitative PCR assays for the specific detection and quantification of<i>Mycobacterium avium</i>subsp.<i>paratuberculosis</i>

2011· article· en· W2163779088 on OpenAlexvenueno aff
Francesca Sidoti, Giuliana Banche, Sara Astegiano, Valeria Allizond, Annamaria Cuffini, Massimiliano Bergallo

Bibliographic record

VenueCanadian Journal of Microbiology · 2011
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsnot available
FundersRegione Piemonte
KeywordsParatuberculosisBiologyIn silicoReal-time polymerase chain reactionMycobacteriumComputational biologyMicrobiologyVirologyGeneticsBacteriaGene

Abstract

fetched live from OpenAlex

Mycobacterium avium subsp. paratuberculosis (Map) is the causative agent of Johne's disease and may contribute to the onset and development of Crohn's disease in humans. Rapid detection of Map is fundamental because of its reported isolation from pasteurized milk and its potential for transmission through environmental sources. In this study, we developed two independent real-time quantitative PCR assays targeting the IS900 genetic insertion sequence and the F57 sequence, which proved capable of detecting and quantifying Map DNA. Validation and standardization of the developed methods were performed by evaluating diagnostic trueness, precision, and accuracy of the techniques. Specificity of the IS900 and F57 methods was verified in both in silico and experimental studies. The assays were found to be very accurate and precise with high repeatability and reproducibility. Moreover, the two real-time assays were very specific for Map, discriminating most of mycobacterial and nonmycobacterial species.

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)0.024
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.037
GPT teacher head0.267
Teacher spread0.229 · 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 designBench or experimental
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

Citations28
Published2011
Admission routes1
Has abstractyes

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