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Record W2161810494 · doi:10.1186/1472-6963-4-38

Systems for grading the quality of evidence and the strength of recommendations I: Critical appraisal of existing approaches The GRADE Working Group

2004· article· en· W2161810494 on OpenAlexaff
David C. Atkins, Martin Eccles, Signe Flottorp, Gordon Guyatt, David Henry, Suzanne Hill, Alessandro Liberati, Dianne L. O’Connell, Andrew D Oxman, Bob Phillips, Holger J. Schünemann, Tessa Tan-Torres Edejer, Gunn Elisabeth Vist, John W Williams

Bibliographic record

VenueBMC Health Services Research · 2004
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGrading (engineering)Critical appraisalMedicineHarmHealth informaticsEvidence-based medicinePsychologyNursingPublic healthSocial psychologyAlternative medicinePathologyEngineering

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.573
metaresearch head score (Gemma)0.801
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.427
Threshold uncertainty score0.527

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5730.801
Meta-epidemiology (narrow)0.0070.007
Meta-epidemiology (broad)0.0150.020
Bibliometrics0.0990.047
Science and technology studies0.0070.018
Scholarly communication0.0270.018
Open science0.0180.021
Research integrity0.0120.018
Insufficient payload (model declined to judge)0.0080.004

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 head0.879
GPT teacher head0.686
Teacher spread0.193 · 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
DomainMethods
GenreEmpirical

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

Citations1,231
Published2004
Admission routes1
Has abstractyes

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