MétaCan
Menu
← Back to cohort
Record W3164937914 · doi:10.1183/13993003.00691-2021

Repeat bronchoalveolar lavage in idiopathic pulmonary fibrosis: proceed with caution?

2021· letter· en· W3164937914 on OpenAlexaff
Mark G. Jones, Martin Kolb

Bibliographic record

VenueEuropean Respiratory Journal · 2021
Typeletter
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIdiopathic pulmonary fibrosisMedicineBronchoalveolar lavageTolerabilityClinical trialPirfenidonePulmonary fibrosisNintedanibInterstitial lung diseaseIntensive care medicineDiseaseInternal medicineOncologyLungAdverse effect

Abstract

fetched live from OpenAlex

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrosing interstitial lung disease with a median life expectancy of 3–5 years [1]. In recent years, management of IPF has been transformed with the worldwide approval of two anti-fibrotic therapies. In parallel, advances in the understanding of IPF pathogenesis have identified numerous targets for potential therapeutic intervention [2]. However, the adoption of anti-fibrotic therapies as the standard of care for patients with IPF has further increased the complexity of investigating novel therapeutics in clinical trials. New, innovative clinical trial design approaches are therefore being implemented. This includes early-phase trials designed not only to inform about drug dosing, safety and tolerability, but also to provide sufficient confidence on target engagement or potential efficacy to support progression to the much more costly later-phase studies. Careful deliberation is required when considering repeat bronchoalveolar lavage in patients with idiopathic pulmonary fibrosis

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)0.002
metaresearch head score (Gemma)0.014
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0260.017
Insufficient payload (model declined to judge)0.0080.011

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 head0.018
GPT teacher head0.241
Teacher spread0.222 · 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
GenreCommentary

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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Respiratory Journal→Same topicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis→French-language works237,207→