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Enregistrement W4405080943 · doi:10.1097/hco.0000000000001191

Editorial introductions

2024· article· en· W4405080943 sur OpenAlexaboutno aff

Notice bibliographique

RevueCurrent Opinion in Cardiology · 2024
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueContemporary Sociological Theory and Practice
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicine

Résumé

récupéré en direct d'OpenAlex

Current Opinion in Cardiology was launched in 1985. 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 cardiology is divided into 14 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 Journal's Editor-in-chief and Section Editors for this issue. EDITOR-IN-CHIEF Subodh VermaSubodh VermaDr Subodh Verma is a cardiac surgeon-scientist, Full Professor, and the Canada Research Chair in Cardiovascular Surgery. He is a Fellow of the Canadian Academy of Health Sciences, a past member of the Royal Society of Canada College of New Scholars, Artists and Scientists, and a past recipient of the Royal College of Physicians and Surgeons of Canada Gold Medal in Surgery. Dr Verma was named a Clarivate Highly Cited Researcher in Clinical Medicine in 2022 and 2023 and was bestowed the University of Calgary Cumming School Medicine Alumnus of Distinction Award for Research in 2023. He is the current Scientific Program Committee Chair for the Canadian Society of Cardiac Surgeons and continues to actively contribute to Canadian clinical practice guidelines. He had/has leadership roles in multiple contemporary global heart failure, cardiometabolic disease, and atherosclerosis trials. Dr Verma founded the CardioLink platform that united cardiac surgeons from across Canada to conduct robust clinical trials to better inform on surgical decision-making pathways. He also leads a dynamic pre-clinical and translational research team that leverages pre-clinical disease models and clinical trial-derived data to identify novel mediators of cardiometabolic diseases. SECTION EDITORS Wilber W. SuWilber W. SuDr Wilber Su is the Director of Cardiac Electrophysiology Banner- University Medical Center and Professor of Medicine at the University of Arizona, USA as well as Stanford University Medical Center, USA. He has a background in biomedical engineering degree from Massachusetts Institute of Technology, USA and received his training at Mayo Clinic Rochester, Minnesota, USA for medicine, cardiology, clinician investigator fellowship, and cardiac electrophysiology. He has been very high-volume operator and has served as training physician in both implantable cardiac devices and complex ablation, notably in atrial fibrillation. He is also active in research with currently multiple important clinical trials and is the national primary investigator for several research trials. He is recognized as the key opinion leader and thought leader around the world as the leader in complex ablation and is a key opinion leader in cryoballoon ablation. He also has taught, presented, and published on various cryoballoon techniques. He has authored “Best Practice Guidelines for Cryoballon Ablation”, and book chapters. In addition, he also serves as a primary teaching center for mapping and ablation of complex arrhythmias. He is also a member of the writing committee for American Heart Association and Heart Rhythm Society national guideline. Dr Su currently serves as the president and governor of the Arizona Chapter of American College of Cardiology. Martin Bødtker MortensenMartin Bødtker MortensenMartin Bødtker Mortensen MD PhD is Associate Professor at the Department of Cardiology at Aarhus University Hospital, Denmark, and Adjunct Associate Professor at the Ciccarone Center for The Prevention of Cardiovascular Disease, Johns Hopkins, Baltimore, USA. Dr Mortensen graduated from the medical school at Aarhus University in 2011 and have since then worked extensively with atherosclerotic cardiovascular disease both clinically and in his research. He obtained his PhD degree in 2015, based on experimental work performed in Dr Jacob Bentzons and Professor Erling Falks laboratory at the Department of Cardiology, Aarhus University Hospital. Dr Mortensen's research field covers both experimental research on the pathogenesis of atherosclerosis as well as epidemiological and clinical studies into the risk and prevention of atherosclerotic cardiovascular disease in humans. Particularly, he has worked extensively on the utility of using non-invasive imaging of subclinical atherosclerosis to identify individuals at low or high risk for development of future clinical disease. Dr Mortensen have published over 100 scientific articles, including in high-impact journals such as Lancet, BMJ, JACC, EHJ, Circulation, JAMA Cardiology and JCI. He is internationally recognized within the field and has received both national and international awards for his research. He has authored several book chapters regarding atherosclerosis, atherosclerotic cardiovascular disease, and dyslipidemias. Dr Mortensen treats patients with lipid disorders, including rare genetic dyslipidemias and familial hypercholesterolemia, in the advanced lipid-clinic at Aarhus University Hospital. Dr Mortensen serves as the chairman for the Preventive Cardiology group in Denmark (under the Danish Society of Cardiology). He has for many years participated in writing the Danish guidelines for treatment of dyslipidemia and prevention of cardiovascular disease issued by the Danish Society of Cardiology and is a regular speaker for the Danish Heart Foundation on the role of cholesterol in the development of atherosclerosis.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,064
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,187
Score d'incertitude au seuil0,626

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,064
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0060,002
Études des sciences et des technologies0,0030,002
Communication savante0,0080,005
Science ouverte0,0030,003
Intégrité de la recherche0,0060,007
Charge utile insuffisante (le modèle a refusé de juger)0,1870,121

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,121
Tête enseignante GPT0,447
Écart entre enseignants0,325 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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