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Record W2255981601 · doi:10.1186/s12916-016-0563-0

Idiopathic pulmonary fibrosis – clinical management guided by the evidence-based GRADE approach: what arguments can be made against transparency in guideline development?

2016· article· en· W2255981601 on OpenAlexaff
Bram Rochwerg, Holger J. Schünemann, Ganesh Raghu

Bibliographic record

VenueBMC Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineGuidelineGrading (engineering)Idiopathic pulmonary fibrosisEvidence-based medicineTransparency (behavior)Intensive care medicineEvidence-based practiceMedical physicsProcess managementPathologyAlternative medicineInternal medicineLungComputer science

Abstract

fetched live from OpenAlex

Evidence-based guidelines have undergone an incredible transformation over the last number of years. Significant advances include explicit linkages of systematic evidence summaries to the strength and direction of recommendations, consideration of all patient-important factors, transparent reporting of the recommendation generation process including conflict of interest management strategies and the production of clinical practice guidelines which use simple and clear language. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology provides a framework for guideline development and was employed to produce the recently published ATS/ERS/JRS/ALAT update on treatment for idiopathic pulmonary fibrosis (IPF). Herein we discuss the advantages of using an evidence-based approach for guideline development using the IPF process and resultant document as an example.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.108
GPT teacher head0.342
Teacher spread0.234 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
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

Citations7
Published2016
Admission routes1
Has abstractyes

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