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Record W4392503562 · doi:10.1097/mol.0000000000000924

Editorial introduction

2024· article· en· W4392503562 on OpenAlexaboutno aff

Bibliographic record

VenueCurrent Opinion in Lipidology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Current Opinion in Lipidology was launched in 1990. It is part of a successful series of review journals whose unique format is designed to provide a systematic and critical assessment of the literature as presented in the many primary journals. The field of lipidology is divided into six sections that are reviewed once a year. Each section is assigned a Section Editor, a leading authority in the area, who identifies the most important topics at that time. Here we are pleased to introduce the Section Editor for this issue. SECTION EDITOR Robert HegeleRobert HegeleDr Rob Hegele is a distinguished University Professor of Medicine and Biochemistry, University of Western Ontario, Canada, and Director of the Lipid Genetics Clinic and the London Regional Genomics Centre in London, Ontario, Canada. He received his MD degree from the University of Toronto in 1981. His specialty training in internal medicine and in endocrinology & metabolism was also in Toronto. His post-doctoral research fellowships were at Rockefeller University, USA, and Howard Hughes Medical Institute, University of Utah, USA. From 1989 to 1997 he was in the Faculty of Medicine at the University of Toronto. In 1997 Dr Hegele joined the Schulich School of Medicine and Dentistry and the Robarts Research Institute at Western University, in London, Ontario, Canada, where he holds the Jacob J. Wolfe Distinguished Medical Research Chair and the Martha Blackburn Chair in Cardiovascular Research. His lab studies the genetics of lipoprotein metabolism, cardiovascular disease and diabetes mellitus. Solely or through collaborations, his lab was first to describe the molecular genetic basis of more than 25 human diseases. His lab has also defined much of the genetic basis of complex disorders, including hypertriglyceridemia. He has co-authored over 780 peer-reviewed publications and has contributed to national treatment guidelines for dyslipidemia, hypertension and diabetes. He is a practicing endocrinologist and has participated in many clinical trials of new lipid drugs. He has trained numerous physicians and graduate students. He received the 2019 American Heart Association Lyman Duff Award and the 2020 Familial Hypercholesterolemia Foundation Pioneer Award.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.073
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.370
Teacher spread0.336 · 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 teacher head, 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

Citations0
Published2024
Admission routes1
Has abstractyes

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