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Systematic reviews of TCM trials: how does inclusion of Chinese trials affect outcome?

2012· article· en· W1544000882 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 Evidence-Based Medicine · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInclusion (mineral)English languageClinical trialChinese languageSystematic reviewMEDLINERandomized controlled trialChinaAlternative medicineMedicineComputer scienceMedical educationPsychologyPathologyLinguisticsSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

AIM: Systematic reviews (SRs) are an important tool for the synthesis of research and are used to guide both research and clinical practice. Previous research suggests that changes to standard SR methodology may be warranted. The objectives of this study were to determine the value of adding Chinese-language databases to conventional systematic review (SR) search strategies, and ii) to determine the importance of methodological validation of TCM RCTs in the conduct of SRs of two health conditions, chronic fatigue syndrome (CFS) and EBV-infectious mononucleosis (mono). METHODS: Ten English-language and two Chinese-language databases were searched from inception to 2008. After initial screening potentially relevant publications were retrieved and assessed based on predetermined inclusion criteria. Method of randomization was verified using author interviews. RESULTS: Mono Search - While English-language database searches did not yield any potentially relevant references, Chinese-language database searches identified 14 studies labelled as RCTs. Author interview determined that 10 were clinical summaries and one a controlled clinical trial. Authors for three publications were unavailable. CFS Search - English-language and Chinese-language database searches identified 8 and 28 potentially relevant references, respectively, for a total of 36, however, none met all inclusion criteria. CONCLUSIONS: Utilization of Chinese-language databases greatly increased the number of potentially relevant references for each search. Unfortunately, due to methodological flaws, this additional information did not generate any usable information. Medical research in China continues to be active, including the conduct of RCTs, however, improvements in trial design and conduct in medical research in China are essential in order for this material to be useful in guiding research and practice.

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: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Meta-analysislow
gptMetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad)
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysismedium
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)0.849
metaresearch head score (Gemma)0.933
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.604
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.8490.933
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0370.009
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.925
GPT teacher head0.642
Teacher spread0.284 · 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