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Record W2784077529 · doi:10.1183/13993003.01312-2017

Pulmonary rehabilitation for patients with COPD during and after an exacerbation-related hospitalisation: back to the future?

2018· letter· en· W2784077529 on OpenAlexaff
Martijn A. Spruit, Sally Singh, Carolyn L. Rochester, Neil Greening, Frits M.E. Franssen, Fábio Pitta, Thierry Troosters, Claire M. Nolan, Ioannis Vogiatzis, Enrico Clini, William D‐C Man, Chris Burtin, Roger Goldstein, Lowie E.G.W. Vanfleteren, Klaus Kenn, Linda Nici, Daisy J.A. Janssen, Richard Casaburi, Takanobu Shioya, Chris Garvey, Brian Carlin, Richard ZuWallack, Michael Steiner, Emiel F.�M. Wouters, Milo A. Puhan

Bibliographic record

VenueEuropean Respiratory Journal · 2018
Typeletter
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
FundersNational Institute for Health and Care Research
KeywordsMedicineExacerbationCOPDGuidelinePulmonary rehabilitationCopd exacerbationPulmonary diseaseRehabilitationIntensive care medicinePhysical therapyHealth professionalsHealth careInternal medicineAcute exacerbation of chronic obstructive pulmonary diseasePathology

Abstract

fetched live from OpenAlex

The European Respiratory Society (ERS) and American Thoracic Society (ATS) guideline on management of chronic obstructive pulmonary disease (COPD) exacerbations was published in the March 2017 issue of the European Respiratory Journal [1]. Based on evidence syntheses, including meta-analyses, relevant evidence up to September 2015 was summarised and clinical recommendations for treatment of COPD exacerbations were formulated. These guidelines were endorsed by the ERS Executive Committee and approved by the ATS Board of Directors in December 2016. Healthcare professionals should educate COPD patients and recommend rehabilitation in the peri-exacerbation period

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)0.004
metaresearch head score (Gemma)0.035
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 score0.031
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0310.023
Insufficient payload (model declined to judge)0.0100.006

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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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

Citations26
Published2018
Admission routes1
Has abstractyes

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