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Record W2789995925 · doi:10.1016/s2213-2600(18)30078-x

Comparison of different treatments for isoniazid-resistant tuberculosis: an individual patient data meta-analysis

2018· review· en· W2789995925 on OpenAlexafffund
Federica Fregonese, Shama D. Ahuja, Onno W. Akkerman, Denise Arakaki-Sánchez, Irene Ayakaka, Parvaneh Baghaei, Didi Bang, Mayara Lisboa Bastos, Andrea Benedetti, Maryline Bonnet, Adithya Cattamanchi, Peter Cegielski, Jung‐Yien Chien, Helen Cox, Martin Dedicoat, Connie Erkens, Patricio Escalante, Dennis Falzon, Anthony J. Garcia‐Prats, Medea Gegia, Stephen H. Gillespie, Judith R. Glynn, Stefan Goldberg, David E. Griffith, Karen R. Jacobson, James C. Johnston, Edward C. Jones‐López, Awal Khan, Won‐Jung Koh, Afrânio Lineu Kritski, Zhi Yi Lan, Jae Ho Lee, Pei Zhi Li, Ethel Leonor Nóia Maciel, Rafael Mello Galliez, Corinne Merle, Melinda Munang, Gopalan Narendran, Viet Nhung Nguyen, Andrew Nunn, Akihiro Ohkado, Jong Sun Park, Patrick Phillips, Ponnuraja Chinnaiyan, Randall Reves, Kamila Romanowski, Kwonjune J. Seung, H. Simon Schaaf, Alena Skrahina, Dick van Soolingen, Payam Tabarsi, Anete Trajman, Lisa Trieu, Banurekha Velayutham, Piret Viiklepp, Jann‐Yuan Wang, Takashi Yoshiyama, Dick Menzies

Bibliographic record

VenueThe Lancet Respiratory Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsBC Centre for Disease ControlUniversity of British ColumbiaMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health ResearchNational Institutes of HealthWorld Health Organization
KeywordsMedicineEthambutolPyrazinamideRifampicinTuberculosisIsoniazidStreptomycinInternal medicineRegimenDrug resistanceSurgeryAntibioticsPathologyMicrobiology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.012
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.026
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0190.049
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.654
GPT teacher head0.550
Teacher spread0.104 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations109
Published2018
Admission routes2
Has abstractno

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