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Record W3006116566 · doi:10.1093/eurheartj/ehz962

Low-density lipoproteins cause atherosclerotic cardiovascular disease: pathophysiological, genetic, and therapeutic insights: a consensus statement from the European Atherosclerosis Society Consensus Panel

2020· article· en· W3006116566 on OpenAlexaff
Jan Borén, M. John Chapman, Ronald M. Krauss, Chris J. Packard, Jacob Fog Bentzon, Christoph J. Binder, Mat J.A.P. Daemen, Linda L. Demer, Robert A. Hegele, Stephen J. Nicholls, Børge G. Nordestgaard, Gerald F. Watts, Éric Bruckert, Sergio Fazio, Brian A. Ference, Ian Graham, Jay D. Horton, Ulf Landmesser, Ulrich Laufs, L. Masana, Gerard Pasterkamp, Frederick J. Raal, Kausik K. Ray, Heribert Schunkert, Marja‐Riitta Taskinen, Bart van de Sluis, Olov Wiklund, Lâle Tokgözoğlu, Alberico L. Catapano, Henry N. Ginsberg

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsWestern University
FundersSteno Diabetes Center AarhusNational Heart, Lung, and Blood InstituteNovo Nordisk FondenEuropean Atherosclerosis Society
KeywordsMedicineConsensus conferenceAtherosclerotic cardiovascular diseaseDiseaseStatement (logic)PathophysiologyBioinformaticsPathologyInternal medicineLaw

Abstract

fetched live from OpenAlex

Abstract

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)0.044
metaresearch head score (Gemma)0.031
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: none
Teacher disagreement score0.044
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0030.003
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0050.003
Research integrity0.0090.014
Insufficient payload (model declined to judge)0.0030.002

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 head0.086
GPT teacher head0.258
Teacher spread0.172 · 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

Citations1,527
Published2020
Admission routes1
Has abstractyes

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