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Record W4214586381 · doi:10.1136/bmj-2022-070533

Increasing the usefulness of acupuncture guideline recommendations

2022· article· en· W4214586381 on OpenAlexaff
Yuqing Zhang, Liming Lu, Nenggui Xu, Xiaorong Tang, Xiaoshuang Shi, Alonso Carrasco‐Labra, Holger J. Schünemann, Yaolong Chen, Jun Xia, Guang Chen, Jianping Liu, Baoyan Liu, Jiyao Wang, Amir Qaseem, Xiang‐Hong Jing, Gordon Guyatt, Hong Zhao

Bibliographic record

VenueBMJ · 2022
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsMcMaster UniversityImpact
FundersGuangzhou UniversityNational Center for Complementary and Integrative HealthGuangzhou University of Chinese MedicineChina Academy of Chinese Medical SciencesNational Natural Science Foundation of China
KeywordsGuidelineAcupunctureMedicineMedical physicsAlternative medicinePathology

Abstract

fetched live from OpenAlex

Acupuncture is the most widely used traditional and complementary medicine, used in 113 of 120 countries according to a 2019 World Health Organization report. In addition to registered acupuncturists, medical doctors, nurse practitioners, and chiropractors occasionally deliver acupuncture treatment. Despite its widespread use and considerable available evidence, until recently, clinical practice guidelines from conventional medical organisations rarely included recommendations on acupuncture. Clinical practice guidelines aim to optimise patient care, 1 and must meet standards of trustworthiness to avoid misleading clinicians, patients, and other stakeholders. We begin by summarising the progress made then address deficiencies that limit the clinical usefulness of acupuncture guidelines, examine the barriers to inclusion of acupuncture in guidelines, and suggest how to overcome them.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.099
GPT teacher head0.390
Teacher spread0.291 · 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

Citations55
Published2022
Admission routes1
Has abstractyes

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