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Record W2059874779 · doi:10.1371/journal.pone.0020185

Epidemiology, Quality and Reporting Characteristics of Systematic Reviews of Traditional Chinese Medicine Interventions Published in Chinese Journals

2011· review· en· W2059874779 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePLoS ONE · 2011
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
FundersUniversity of AlbertaLanzhou University
KeywordsSystematic reviewMedicinePsychological interventionEpidemiologyMEDLINEAlternative medicineSpecialtyMeta-analysisData extractionFamily medicinePublication biasChinaQuality (philosophy)PathologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Systematic reviews (SRs) of TCM have become increasingly popular in China and have been published in large numbers. This review provides the first examination of epidemiological characteristics of these SRs as well as compliance with the PRISMA and AMSTAR guidelines. OBJECTIVES: To examine epidemiological and reporting characteristics as well as methodological quality of SRs of TCM published in Chinese journals. METHODS: Four Chinese databases were searched (CBM, CSJD, CJFD and Wanfang Database) for SRs of TCM, from inception through Dec 2009. Data were extracted into Excel spreadsheets. The PRISMA and AMSTAR checklists were used to assess reporting characteristics and methodological quality, respectively. RESULTS: A total of 369 SRs were identified, most (97.6%) of which used the terms systematic review or meta-analysis in the title. None of the reviews had been updated. Half (49.8%) were written by clinicians and nearly half (47.7%) were reported in specialty journals. The impact factors of 45.8% of the journals published in were zero. The most commonly treated conditions were diseases of the circulatory and digestive disease. Funding sources were not reported for any reviews. Most (68.8%) reported information about quality assessment, while less than half (43.6%) reported assessing for publication bias. Statistical mistakes appeared in one-third (29.3%) of reviews and most (91.9%) did not report on conflict of interest. CONCLUSIONS: While many SRs of TCM interventions have been published in Chinese journals, the quality of these reviews is troubling. As a potential key source of information for clinicians and researchers, not only were many of these reviews incomplete, some contained mistakes or were misleading. Focusing on improving the quality of SRs of TCM, rather than continuing to publish them in great quantity, is urgently needed in order to increase the value of these studies.

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
gemmaMetaresearchMeta-epidemiology (broad)
Domain: Reporting · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptMetaresearchMeta-epidemiology (broad)
Domain: Reporting · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
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)0.561
metaresearch head score (Gemma)0.874
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.313
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5610.874
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0690.007
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.977
GPT teacher head0.651
Teacher spread0.326 · 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