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Record W2163264591 · doi:10.1136/ebm.11.1.2-a

An emerging consensus on grading recommendations?

2006· article· en· W2163264591 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvidence-Based Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGrading (engineering)ExcellenceHealth careEvidence-based medicineRating systemMedicineQuality (philosophy)Quality management systemEvidence-based practiceMedical educationQuality managementPsychologyOperations managementAlternative medicinePolitical scienceEngineeringManagement system

Abstract

fetched live from OpenAlex

Clinical practice guidelines have improved in quality over the past 10 years by adhering to a few basic principles, such as conducting thorough systematic reviews of relevant evidence and grading the recommendations and the quality of the underlying evidence. The large number of systems of measuring the quality of evidence and recommendations that have emerged are, however, confusing.1 The mission of the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) working group is to help resolve the confusion among the different systems of rating evidence and recommendations. The group has wide representation from many organisations including the Agency for Healthcare Research and Quality in the US, the National Institute for Clinical Excellence for England and Wales, and the World Health Organization. Developing a new uniform rating system is challenging because all systems have limitations and because many organisations have invested a great deal of time and effort to develop their rating systems and are understandably reluctant to adopt a new system. The GRADE working group first published the results of its work in 2004 in the BMJ.2 A simpler, clinically oriented description will soon be published.3 GRADE has taken care to ensure its suggested system is simple to use and applicable to a wide variety of clinical recommendations that span the full spectrum of medical specialties and clinical care. The GRADE system classifies recommendations in 1 of 2 levels—strong and weak—and quality of evidence into 1 of 4 levels—high, moderate, low, and very low. Evidence based on randomised controlled trials (RCTs) begins with a top rating on GRADE’s 4 level quality of evidence classification (table …

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.587
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.424
GPT teacher head0.540
Teacher spread0.115 · 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