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Record W2125913020 · doi:10.1016/s0140-6736(12)60480-2

Effectiveness of quality improvement strategies on the management of diabetes: a systematic review and meta-analysis

2012· review· en· W2125913020 on OpenAlexafffund
Andrea C. Tricco, Noah Ivers, Jeremy Grimshaw, David Moher, Lucy Turner, James Galipeau, Ilana Halperin, Brigitte Vachon, Tim Ramsay, Braden Manns, Marcello Tonelli, Kaveh G Shojania

Bibliographic record

VenueThe Lancet · 2012
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of CalgaryUniversité de MontréalLibin Cardiovascular Institute of AlbertaUniversity of OttawaOttawa HospitalUniversity of TorontoWomen's College HospitalSt. Michael's Hospital
FundersCanada Research ChairsCanadian Institutes of Health ResearchAlberta Innovates - Health SolutionsUniversity of Ottawa
KeywordsMedicineBlood pressureDiabetes mellitusClinical trialMeta-analysisAspirinInternal medicineRandomized controlled trialMEDLINEDiabetes managementPhysical therapyType 2 diabetes

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.042
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0170.025
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.175
GPT teacher head0.406
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations653
Published2012
Admission routes2
Has abstractno

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