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Record W2986894253 · doi:10.1016/j.gheart.2019.09.003

Strategic, Successful, and Sustained Synergy: The Global Alliance for Chronic Diseases Hypertension Program

2019· editorial· en· W2986894253 on OpenAlexafffund
Ruth Webster, Gary Parker, Stéphane Héritier, Rohina Joshi, Karen Yeates, Patricio López‐Jaramillo, J. Jaime Miranda, Brian Oldenburg, Bruce Ovbiagele, Mayowa Owolabi, David Peiris, Devarsetty Praveen, Abdul Salam, Jon-David Schwalm, Kavumpurathu Raman Thankappan, Nihal Thomas, Sheldon W. Tobe, Rajesh Vedanthan

Bibliographic record

VenueGlobal Heart · 2019
Typeeditorial
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsNOSM UniversityPopulation Health Research InstituteMcMaster UniversityHamilton Health SciencesHealth Sciences CentreSunnybrook Health Science Centre
FundersChristian Medical College, VelloreMonash UniversityUniversidad de SantanderSree Chitra Tirunal Institute for Medical Sciences and TechnologyUniversity of New South WalesYork UniversityQueen's UniversityMcMaster UniversityUniversity of California, San FranciscoHamilton Health Sciences
KeywordsMedicineChecklistAllianceGlobal healthObservational studyStrengthening the reporting of observational studies in epidemiologyEpidemiologyMedical educationPublic healthFamily medicinePolitical sciencePathologyPsychology

Abstract

fetched live from OpenAlex

Global Heart is the official and primary publication of the World Heart Federation, offering a platform for the dissemination of knowledge on research, developments, trends, solutions and public health programmes in the area of cardiovascular disease. Global Heart welcomes research results, points of view and educational material on the prevention, treatment and control of cardiovascular disease with a special focus on low and middle-income countries which are facing the brunt of epidemiological transition.Global Heart strongly encourages authors to adhere to CONSORT, STROBE, STARD, and PRISMA guidelines for reporting of clinical trials, observational studies, diagnostic test accuracy papers, and systematic reviews or meta-analyses. Authors are required for submission to download and complete the appropriate Equator Network checklist: http://www.equator-network.org/.

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.

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)0.022
metaresearch head score (Gemma)0.077
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.022
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.077
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0100.005
Open science0.0020.003
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0220.013

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 head0.021
GPT teacher head0.319
Teacher spread0.298 · 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
GenreEditorial

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

Citations8
Published2019
Admission routes2
Has abstractyes

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