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Record W4389951840 · doi:10.1097/mol.0000000000000912

Editorial introductions

2023· article· en· W4389951840 on OpenAlexaboutno aff

Bibliographic record

VenueCurrent Opinion in Lipidology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicContemporary Sociological Theory and Practice
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 Editor and Section Editors for this issue. EDITOR Robert A HegeleRobert A HegeleRob 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 on 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 the 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, cardio¬vascular disease and diabetes mellitus. Solely or through collaborations, his lab was first to describe the molecular genetic basis of 20 human diseases. His lab has also defined much of the genetic basis of complex disorders, including hypertriglyceridemia. He has co-authored over 600 peer-reviewed publications and has contributed to national treatment guidelines for dyslipidemia, hypertension and diabetes. He is a practicing endocrinologist and has participated in numerous clinical trials. He has trained numerous physicians and graduate students. SECTION EDITORS Majken K. JensenMajken K. Jensen, PhD, is Associate Professor of Nutrition and Epidemiology at Harvard T. H. Chan School of Public Health. Dr Jensen's primary research interests include novel metabolic markers, nutrition, and genetics, in relation to chronic lifestyle diseases. In ongoing collaborations with Dr Frank Sacks, they investigate how the presence of a small proinflammatory protein (apolipoprotein C-III) on HDL particles marks a potentially dysfunctional type of HDL that is not inversely associated with risk of cardiometabolic health, such as IMT, diabetes and cardiovascular disease. Other currently funded work is focused on lipoprotein metabolism and Alzheimer's disease and stroke. Her research predominantly utilizes large-scale observational studies (including the Health Professionals Follow-Up Study, the Nurses’ Health Study, the Danish Diet, Cancer and Health study, the Multi-Ethnic Study of Atherosclerosis, and the Cardiovascular Health Study) where cost-efficient prospective case-control studies are nested within for purpose of measuring novel biomarkers or genome-wide markers. Dr Jensen's research has been published in leading scientific journals and has been recognized with numerous awards. She received the Trudy Bush Fellowship for Cardiovascular Disease Research in Women's Health from the American Heart Association in 2011 and originally came for research studies at Harvard T. H. Chan School of Public Health as a Fulbright scholar. Dr Jensen has published over 80 original research articles and 5 reviews, editorials, and letters. Marta Guasch-FerréMarta Guasch-FerréDr. Guasch-Ferré is an Associate Professor and Group Leader at the Department of Public Health and Novo Nordisk Center for Basic Metabolic Research at the University of Copenhagen, Denmark. She also holds an appointment as Adjunct Associate Professor at the Department of Nutrition at Harvard T.H. Chan School of Public Health, U.S. Her research focuses on nutritional and lifestyle epidemiology and prevention of type 2 diabetes (T2D) and cardiovascular disease (CVD). She has incorporated high-throughput –omics techniques, particularly metabolomics, into traditional epidemiological analysis to gain insights into underlying mechanisms that could explain the associations between lifestyle factors in relation to CVD and T2D. She has been involved in the design and implementation of several clinical trials including the well-known PREDIMED trial, a primary cardiovascular prevention trial. She currently works on large prospective cohort studies on the Nurses’ Health Study and the Health Professional's Follow-up Study. Her research activities have resulted in numerous manuscripts (>130, H-index 43), and she has been awarded with various competitive European and American grants. Dr. Guasch-Ferré was the recipient of the Sandra A. Daugherty Award for Excellence in Cardiovascular Disease or Hypertension Epidemiology and Prevention by the American Heart Association (2021). She serves as the P.I. of a NIH-funded project entitled ‘Circulating plasma metabolites, lifestyle factors, and mortality risk’. She is also an investigator in two NIH-funded projects to study Mediterranean dietary interventions, plasma metabolites, and the risk of CVD and T2D.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.141
Threshold uncertainty score0.922

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.193
GPT teacher head0.462
Teacher spread0.270 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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