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Record W1777587551 · doi:10.1016/s0140-6736(15)00469-9

Availability and affordability of cardiovascular disease medicines and their effect on use in high-income, middle-income, and low-income countries: an analysis of the PURE study data

2015· article· en· W1777587551 on OpenAlexafffund
Rasha Khatib, Martin McKee, Harry S. Shannon, Clara K Chow, Sumathy Rangarajan, Koon Teo, Wei Li, Prem Mony, Viswanathan Mohan, Rajeev Gupta, Rajesh Kumar, Krishnapillai Vijayakumar, Scott A. Lear, Rafael Díaz, Álvaro Avezum, Patricio López‐Jaramillo, Fernando Laņas, Khalid Yusoff, Noor Hassim Ismail, Khawar Kazmi, Omar Rahman, Annika Rosengren, Nahed Monsef, Roya Kelishadi, Annamarie Kruger, Thandi Puoane, Andrzej Szuba, Jephat Chifamba, Ahmet Temizhan, Gilles R. Dagenais, Amiram Gafni, Salim Yusuf

Bibliographic record

VenueThe Lancet · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsSimon Fraser UniversityUniversité LavalHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
FundersCanadian Institutes of Health ResearchInternational Development Research CentreHeart and Stroke Foundation of Canada
KeywordsPharmacyMedicineEnvironmental healthDiseaseMiddle incomeRural areaSocioeconomicsBusinessEconomicsDemographic economicsFamily 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)0.009
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.008
Bibliometrics0.0020.006
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.089
GPT teacher head0.297
Teacher spread0.208 · 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 designObservational
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

Citations394
Published2015
Admission routes2
Has abstractno

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