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Record W4393084601 · doi:10.1016/j.lanwpc.2024.101014

Developing best practice public health standards for whole genome sequencing of Mycobacterium tuberculosis

2024· article· en· W4393084601 on OpenAlexaff
Justin T. Denholm, Marcel A. Behr, Gèrard de Vries, Richard Anthony, Esther Robinson, Matthijs Backx, Ian F. Laurenson, Amie-Louise Seagar, Herns Modestil, Lisa Trieu, Jeanne Sullivan Meissner, Deborah Hee Ling Ng, Jun Yang Tay, Hsien-Ho Lin, Robyn S. Lee, Ellen Donnan, Vitali Sintchenko, Ben J. Marais

Bibliographic record

VenueThe Lancet Regional Health - Western Pacific · 2024
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMycobacterium tuberculosisWhole genome sequencingPublic healthGenomeTuberculosisVirologyBiologyBest practiceComputational biologyMicrobiologyMedicineGeneticsGenePolitical scienceNursingPathology

Abstract

fetched live from OpenAlex

Mycobacterium tuberculosis is a priority pathogen for global control. A growing number of countries have begun to incorporate routine whole genome sequencing (WGS) to support key aspects of tuberculosis (TB) public health and clinical practice, including monitoring of laboratory and clinical practices, detection and surveillance of drug resistance, and guidance of targeted public health interventions such as expanded contact investigation and active case finding. However, enhanced structures, workforce capacity and monitoring systems are required to support effective translation of pathogen genomics into clinical and public health practice.

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)0.394
metaresearch head score (Gemma)0.485
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.394
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3940.485
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0130.009
Science and technology studies0.0050.013
Scholarly communication0.0210.015
Open science0.0210.022
Research integrity0.0240.035
Insufficient payload (model declined to judge)0.0070.007

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 head0.202
GPT teacher head0.444
Teacher spread0.242 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueThe Lancet Regional Health - Western Pacific→Same topicTuberculosis Research and Epidemiology→French-language works237,207→