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Record W2602895493 · doi:10.15326/jcopdf.4.2.2017.0128

The COPD Biomarkers Qualification Consortium Database: Baseline Characteristics of the St George’s Respiratory Questionnaire Dataset

2017· article· en· W2602895493 on OpenAlexaff
Maggie Tabberer, Victoria S. Benson, Heather L. Gelhorn, Hilary Wilson, Niklas Karlsson, Hana Müllerová, Shailendra Menjoge, Stephen I. Rennard, Ruth Tal‐Singer, Debora Merrill, Paul Jones

Bibliographic record

VenueChronic Obstructive Pulmonary Diseases Journal of the COPD Foundation · 2017
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsQuest University Canada
FundersGlaxoSmithKlineCOPD FoundationAstraZenecaPfizer
KeywordsObservational studyMedicineContext (archaeology)COPDQuality of life (healthcare)Physical therapyDatabaseInternal medicine

Abstract

fetched live from OpenAlex

<0.0001) and this observation held across studies. SGRQ scores increased with increasing modified Medical Research Council dyspnea scores (mean differences ranged 6.9-17.9 units) and with increasing airflow limitations (Global initiative for chronic Obstructive Lung Disease grades 1 to 4; differences ranged 4.5-16.1 units), consistent across study types. As a method of cross-sectional comparison, the SGRQ appears to be relatively free of bias from demographic factors although care should be taken when making cross sectional comparisons of scores between patients in countries at different levels of socio-economic development/.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.016
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.008

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 head0.026
GPT teacher head0.322
Teacher spread0.296 · 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 designObservational
Domainnot available
GenreDataset

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

Citations9
Published2017
Admission routes1
Has abstractyes

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