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Record W2027974152 · doi:10.1016/j.ahj.2004.08.033

Challenges in the conduct of large simple trials of important generic questions in resource-poor settings: The CREATE and ECLA trial program evaluating GIK (glucose, insulin and potassium) and low-molecular-weight heparin in acute myocardial infarction

2004· article· en· W2027974152 on OpenAlexafffund
Salim Yusuf, Shamir R. Mehta, Rafael Díaz, Ernesto Paolasso, Prem Pais, Denis Xavier, Changchun Xie, Rashid Ahmed, Khawar Khazmi, Jun Zhu, Lisheng Liu

Bibliographic record

VenueAmerican Heart Journal · 2004
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsMcMaster UniversityPopulation Health Research InstituteHamilton General Hospital
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsMedicineRandomized controlled trialMyocardial infarctionPlaceboClinical trialLow molecular weight heparinInternal medicineIntensive care medicineEmergency medicineHeparinPathologyAlternative medicine

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)0.485
metaresearch head score (Gemma)0.451
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.485
Threshold uncertainty score0.636

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4850.451
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0100.007
Bibliometrics0.0010.003
Science and technology studies0.0040.008
Scholarly communication0.0100.008
Open science0.0050.005
Research integrity0.0100.016
Insufficient payload (model declined to judge)0.0060.002

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 head0.061
GPT teacher head0.388
Teacher spread0.327 · 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.

Study designNon-randomized trial
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

Citations43
Published2004
Admission routes2
Has abstractno

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