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Record W2803833837 · doi:10.1016/j.jcct.2018.05.011

Impact of Non-obstructive left main disease on the progression of coronary artery disease: A PARADIGM substudy

2018· article· en· W2803833837 on OpenAlexaff
Jonathan Weir‐McCall, Philipp Blanke, Stephanie Sellers, Amir Ahmadi, Daniele Andreini, Matthew J. Budoff, Filippo Cademartiri, Kavitha M. Chinnaiyan, Jung Hyun Choi, Eun Ju Chun, Edoardo Conte, Ilan Gottlieb, Martin Hadamitzky, Byoung Kwon Lee, Sang‐Eun Lee, Erica Maffei, Hugo Marques, Gianluca Pontone, Gilbert Raff, Sanghoon Shin, Ji Min Sung, Peter H. Stone, Habib Samady, Renu Virmani, Jagat Narula, Daniel S. Berman, Leslee J. Shaw, Jeroen J. Bax, Fay Y. Lin, James K. Min, Hyuk‐Jae Chang, Jonathon Leipsic

Bibliographic record

VenueJournal of cardiovascular computed tomography · 2018
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersGE HealthcareBiotronikMinistry of Science, ICT and Future PlanningNational Research Foundation of KoreaMedtronicDalio FoundationNational Institutes of HealthBoston Scientific CorporationNational Research FoundationEdwards LifesciencesBracco Group
KeywordsMedicineCardiologyLeft main coronary artery diseaseInternal medicineCoronary artery diseaseArteryBypass grafting

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)0.002
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.280
Teacher spread0.268 · 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

Citations18
Published2018
Admission routes1
Has abstractno

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