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Record W2077290403 · doi:10.1378/chest.14-2506

Tools for Assessing Outcomes in Studies of Chronic Cough

2014· article· en· W2077290403 on OpenAlexaff
Louis‐Philippe Boulet, Remy R Coeytaux, Douglas C McCrory, Cynthia T. French, Anne B. Chang, Surinder S. Birring, John A. Smith, Rebecca L. Diekemper, Bruce K. Rubin, Richard S. Irwin, Todd M. Adams, Kenneth W. Altman, Alan F. Barker, Fiona Blackhall, Donald C. Bolser, Sidney S. Braman, Christopher E. Brightling, Priscilla Callahan-Lyon, Terrie Cowley, Paul W. Davenport, Satoru Ebihara, Ali A. El Solh, Patricio Escalante, Anthony Feinstein, Stephen K. Field, Dina Fisher, Peter G. Gibson, Philip Gold, Michael K. Gould, Cameron Grant, Susan M. Harding, Anthony Harnden, Adam T. Hill, Peter J. Kahrilas, Karina A. Keogh, Andrew P. Lane, Sandra Zelman Lewis, Kaiser G. Lim, Mark A. Malesker, Stuart B. Mazzone, Lorcan McGarvey, M. Hassan Murad, Peter Newcombe, Huong Q. Nguyen, John Oppenheimer, David J. Prezant, Marcos I. Restrepo, Mark J. Rosen, Jay H. Ryu, Susan M. Tarlo, Anne E. Vertigan, Gang Wang, Miles Weinberger, Kelly A. Weir

Bibliographic record

VenueCHEST Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineChronic coughQuality of life (healthcare)Physical therapyMEDLINEIntensive care medicineFamily medicineAsthmaInternal medicineNursing

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)0.142
metaresearch head score (Gemma)0.291
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score0.753

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1420.291
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0070.016
Bibliometrics0.0270.020
Science and technology studies0.0030.002
Scholarly communication0.0060.007
Open science0.0030.012
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.175
GPT teacher head0.451
Teacher spread0.276 · 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 designTheoretical or conceptual
DomainMethods
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

Citations134
Published2014
Admission routes1
Has abstractno

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