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Improving benefit-harm assessment of glucocorticoid therapy incorporating the patient perspective: The OMERACT glucocorticoid core domain set

2021· article· en· W3177286686 on OpenAlexaff
Joanna Tieu, Jonathan TL. Cheah, Rachel Black, Robin Christensen, Nilasha Ghosh, Pamela Richards, Joanna Robson, Beverley Shea, Lee S. Simon, Jasvinder A Singhi, Peter Tugwell, Maarten Boers, Marco A Alba Garibay, Corrado Campochiaro, Simon Décary, Maarten de Witt, Anthony P. Fernandez, Helen Keen, Lauren King, Andrea Hinojosa‐Azaola, C. Richard Hofstetter, I. Z. Gaydukova, Michael George, Latika Gupta, Suellen Anne Lyne, Ashima Makol, Chetan Mukhtyar, Win Min Oo, Michelle Petri, Huai Leng Pisaniello, Sebastian E. Sattui, Oscar Russell, Vítor Teixeira, Karine Toupin‐April, Courage Uhunmwangho, Margaret T. Whitstock, Kevin Yip, Sarah Mackie, Susan M. Goodman, Catherine Hill

Bibliographic record

VenueSeminars in Arthritis and Rheumatism · 2021
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsChildren's Hospital of Eastern OntarioUniversité de SherbrookeUniversity of TorontoOttawa Public HealthOttawa HospitalBruyèreUniversity of Ottawa
FundersNational Institute for Health and Care Research
KeywordsMedicineGlucocorticoidPerspective (graphical)Set (abstract data type)Core (optical fiber)HarmIntensive care medicineInternal medicineArtificial intelligenceSocial psychology

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)0.015
metaresearch head score (Gemma)0.064
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.064
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.301
Teacher spread0.286 · 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
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

Citations12
Published2021
Admission routes1
Has abstractno

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