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Methods for living guidelines: early guidance based on practical experience. Paper 5: decisions on methods for evidence synthesis and recommendation development for living guidelines

2023· article· en· W4313531161 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

VenueJournal of Clinical Epidemiology · 2023
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster UniversityImpact
FundersDavid and Elaine Potter FoundationAustralasian Paediatric Endocrine GroupAustralian Diabetes Educators AssociationIan Potter FoundationAustralian GovernmentState Government of VictoriaAustralian Diabetes SocietyEquity TrusteesDiabetes AustraliaDepartment of Health and Social CareInfectious Diseases Society of AmericaU.S. Department of Health and Human Services
KeywordsGuidelineProcess (computing)Context (archaeology)Process managementManagement scienceMedicineIdentification (biology)Risk analysis (engineering)Computer scienceBusinessEngineeringPathologyEcology

Abstract

fetched live from OpenAlex

OBJECTIVES: Producing living guidelines requires making important decisions about methods for evidence identification, appraisal, and integration to allow the living mode to function. Clarifying what these decisions are and the trade-offs between options is necessary. This article provides living guideline developers with a framework to enable them to choose the most suitable model for their living guideline topic, question, or context. STUDY DESIGN AND SETTING: We developed this guidance through an iterative process informed by interviews, feedback, and a consensus process with an international group of living guideline developers. RESULTS: Several key decisions need to be made both before commencing and throughout the continual process of living guideline development and maintenance. These include deciding what approach is taken to the systematic review process; decisions about methods to be applied for the evidence appraisal process, including the use of unpublished data; and selection of "triggers" to incorporate new studies into living guideline recommendations. In each case, there are multiple options and trade-offs. CONCLUSION: We identify trade-offs and important decisions to be considered throughout the living guideline development process. The most appropriate, and most sustainable, mode of development and updating will be dependent on the choices made in each of these areas.

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.

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)0.237
metaresearch head score (Gemma)0.980
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2370.980
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.868
GPT teacher head0.747
Teacher spread0.121 · 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