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Record W2793567629 · doi:10.1183/13993003.00170-2018

Treatment outcome definitions in nontuberculous mycobacterial pulmonary disease: an NTM-NET consensus statement

2018· editorial· en· W2793567629 on OpenAlexaff
Jakko van Ingen, Timothy R. Aksamit, C. Andréjak, Erik C. Böttger, Emmanuelle Cambau, Charles L. Daley, David E. Griffith, Lorenzo Guglielmetti, Steven M. Holland, Gwen A. Huitt, Won‐Jung Koh, Christoph Lange, Philip Leitman, Theodore K. Marras, Kozo Morimoto, Kenneth N. Olivier, Miguel Santín, Jason E. Stout, Rachel Thomson, Enrico Tortoli, Richard J. Wallace, Kevin Winthrop, Dirk Wagner

Bibliographic record

VenueEuropean Respiratory Journal · 2018
Typeeditorial
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Institutes of HealthNHLBI Division of Intramural ResearchNederlandse Organisatie voor Wetenschappelijk OnderzoekZonMwEuropean Society of Clinical Microbiology and Infectious DiseasesAmerican Thoracic SocietySavara PharmaceuticalsInsmedGilead SciencesAstraZenecaEuropean Respiratory Society
KeywordsMedicineBronchiectasisNontuberculous mycobacteriaIntensive care medicineDiseaseTuberculosisInfectious disease (medical specialty)Lung diseasePopulationPulmonary diseaseFamily medicineLungInternal medicineMycobacteriumPathologyEnvironmental health

Abstract

fetched live from OpenAlex

Nontuberculous mycobacterial pulmonary diseases (NTM-PD) are increasingly recognised as opportunistic infections of humans. These chronic pulmonary infections have two main presentations. The first is a fibro-cavitary disease, that occurs in patients with pre-existing pulmonary diseases, such as chronic obstructive pulmonary disease, bronchiectasis, previous tuberculosis or other structural lung disease. The second presentation is a nodular-bronchiectatic disease of primarily the lingula and middle lobe that tends to affect a middle-aged and elderly female population [1]. Improving treatment outcome reporting in NTM disease: NTM-NET (@ntmnet) consensus statement on treatment outcome definitions <http://ow.ly/c6IC30iwLM4> The authors wish to thank the American Thoracic Society, European Respiratory Society, Infectious Diseases Society of America and European Society of Clinical Microbiology and Infectious Diseases for organising the two meetings during which the process leading to this statement was initiated. These organisations do not officially endorse this NTM-NET consensus statement.

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)0.035
metaresearch head score (Gemma)0.089
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.035
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.089
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0040.003
Research integrity0.0110.020
Insufficient payload (model declined to judge)0.0030.003

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 head0.079
GPT teacher head0.352
Teacher spread0.273 · 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
GenreEditorial

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

Citations263
Published2018
Admission routes1
Has abstractyes

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