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Record W1987418479 · doi:10.1016/j.ahj.2014.07.029

Rationale and design of a randomized controlled trial evaluating community health worker–based interventions for the secondary prevention of acute coronary syndromes in India (SPREAD)

2014· article· en· W1987418479 on OpenAlexaff
Deepak Kamath, Denis Xavier, Rajeev Gupta, P.J. Devereaux, Alben Sigamani, Tanvir Hussain, Sowmya Umesh, Freeda Xavier, P.V. Girish, Nisha George, Tinku Thomas, Natarajan Chidambaram, Rajnish Joshi, Prem Pais, Salim Yusuf

Bibliographic record

VenueAmerican Heart Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsHeart and Stroke FoundationHamilton Health SciencesPopulation Health Research InstituteMcMaster University
FundersU.S. Public Health ServiceNational Heart, Lung, and Blood InstituteUnitedHealth Group
KeywordsMedicineUnstable anginaBody mass indexPsychological interventionRandomized controlled trialMyocardial infarctionBlood pressureAcute coronary syndromePhysical therapyDiabetes mellitusAnginaEmergency medicineInternal medicineNursing

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)0.085
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.085
Threshold uncertainty score0.449

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0850.063
Meta-epidemiology (narrow)0.0070.004
Meta-epidemiology (broad)0.0090.007
Bibliometrics0.0030.002
Science and technology studies0.0030.007
Scholarly communication0.0050.003
Open science0.0030.002
Research integrity0.0100.008
Insufficient payload (model declined to judge)0.0200.004

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 head0.083
GPT teacher head0.440
Teacher spread0.357 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations23
Published2014
Admission routes1
Has abstractno

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