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Control of Confounding and Reporting of Results in Causal Inference Studies. Guidance for Authors from Editors of Respiratory, Sleep, and Critical Care Journals

2018· article· en· W2891367027 on OpenAlexaff
David J. Lederer, Scott C. Bell, Richard D. Branson, James D. Chalmers, Rachel Marshall, David M. Maslove, David E. Ost, Naresh M. Punjabi, Michael Schätz, Alan R Smyth, Paul W. Stewart, Samy Suissa, Alex A. Adjei, Cezmi A. Akdiş, Élie Azoulay, Jan Bakker, Zuhair K. Ballas, Philip G. Bardin, Esther Barreiro, Rinaldo Bellomo, Jonathan A. Bernstein, Vito Brusasco, Timothy G. Buchman, Sudhansu Chokroverty, Nancy A. Collop, James D. Crapo, Dominic A. Fitzgerald, Lauren Hale, Nicholas Hart, Felix Herth, Theodore J. Iwashyna, Gísli Jenkins, Martin Kolb, Guy B. Marks, Peter J. Mazzone, J. Randall Moorman, Thomas M. Murphy, Terry L. Noah, Paul N. Reynolds, Dieter Riemann, Richard Russell, Aziz Sheikh, Giovanni Sotgiu, Erik R. Swenson, Rhonda D. Szczesniak, Ronald Szymusiak, Jean–Louis Teboul, Jean‐Louis Vincent

Bibliographic record

VenueAnnals of the American Thoracic Society · 2018
Typearticle
Languageen
FieldMathematics
TopicAdvanced Causal Inference Techniques
Canadian institutionsMcMaster UniversityMcGill UniversityQueen's University
Fundersnot available
KeywordsConfoundingCausal inferenceFallacyMedicineStatisticsEconometricsComputer scienceMathematicsLinguistics

Abstract

fetched live from OpenAlex

International audience

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)0.719
metaresearch head score (Gemma)0.926
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.281
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7190.926
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0080.004
Bibliometrics0.0150.013
Science and technology studies0.0060.020
Scholarly communication0.0200.024
Open science0.0140.012
Research integrity0.0200.029
Insufficient payload (model declined to judge)0.0120.010

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 head0.409
GPT teacher head0.575
Teacher spread0.166 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreMethods

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

Citations722
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the American Thoracic SocietySame topicAdvanced Causal Inference TechniquesFrench-language works237,207