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Record W2108020394 · doi:10.1210/jc.2013-1814

The Endocrine Society Guidelines: When the Confidence Cart Goes Before the Evidence Horse

2013· article· en· W2108020394 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

VenueThe Journal of Clinical Endocrinology & Metabolism · 2013
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster UniversityInstitute of Nutrition, Metabolism and Diabetes
Fundersnot available
KeywordsGuidelineGrading (engineering)Confidence intervalMedicinePsychologyFamily medicineInternal medicinePathologyBiology

Abstract

fetched live from OpenAlex

CONTEXT: In 2005, the Endocrine Society (TES) adopted the GRADE system of developing clinical practice guidelines. Grading of Recommendations, Assessment, Development, and Evaluation working group guidance suggests that strong recommendations based on low or very low (L/VL) confidence may often be inappropriate, and has offered a taxonomy of paradigmatic situations in which strong recommendations based on L/VL confidence estimates may be appropriate. OBJECTIVE: We sought to characterize strong recommendations of TES based on L/VL confidence evidence. DATA SOURCES AND EXTRACTION: We identified all strong recommendations based on L/VL confidence evidence published in TES guidelines between 2005 and 2011. We identified those consistent with one of the paradigmatic situations in the taxonomy. DATA SYNTHESIS: Two hundred six of 357 (58%) of the recommendations of TES were strong; of these, 121 (59%) were based on L/VL confidence evidence. Of these 121, 35 (29%) were consistent with one of the paradigmatic situations. The most common situation (13, 11%) was of a strong recommendation against the intervention because of low confidence evidence for benefit and high confidence evidence for harm. The remaining 86 (71%) comprised 43 (36%) "best practice" statements for which sensible alternatives do not exist; 5 (4%) in which recommendations were for "additional research"; 5 (4%) in which greater confidence in the estimates was warranted; and 33 (27%) for which we could not find a compelling explanation for the incongruence. CONCLUSIONS: Guideline panels should beware of formulating strong recommendations when confidence in estimates is low. Our taxonomy when such recommendations are appropriate may be helpful.

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)0.017
metaresearch head score (Gemma)0.103
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
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 score0.576
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.103
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.342
GPT teacher head0.529
Teacher spread0.187 · 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