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Record W4234099691 · doi:10.1097/med.0000000000000327

Editorial introductions

2017· article· en· W4234099691 on OpenAlexaboutno aff

Bibliographic record

VenueCurrent Opinion in Endocrinology Diabetes and Obesity · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsnot available
Fundersnot available
KeywordsInternshipBachelorLibrary scienceNavyMedicineSection (typography)Medical educationFamily medicineGerontologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Current Opinion in Endocrinology and Diabetes was launched in 1994, with Obesity added to the title in 2007. It is one 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 fields of endocrinology and diabetes are divided into 12 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 one of the Journal's Section Editors for this issue. SECTION EDITORS David M. HarlanDavid M. HarlanDr David M. Harlan is a graduate of the University of Michigan (Bachelor of Science) and the Duke University School of Medicine, USA. He completed his internal medicine internship and residency at the Duke University Medical Center. This was before serving for four years as a staff internist at the Navy Hospital, San Diego, CA, USA. He then returned to Duke for his fellowship training in diabetes, endocrinology, and metabolism. In 1991 he established his laboratory at the Navy Medical Research Institute, USA, where he rose to become the Director of Combat Casualty Care. He was then appointed to the faculty of the Uniformed Services University of the Health Sciences. In 1999, he moved his laboratory to the National Institutes of Health, where he became the Diabetes Branch Chief within the National Institute of Diabetes, Digestive, and Kidney Diseases. In 2010, he moved to the University of Massachusetts School of Medicine, USA, where he is the William and Doris Krupp Professor of Medicine. Dr Harlan co-directs the university's Diabetes Center of Excellence. His research interests all relate to diabetes and include the immunopathogenesis underlying type 1 diabetes and improved care delivery models, including transplant-based approaches, for the disease. Dan StrejaDan StrejaDr Dan Streja is Clinical Professor of Medicine at David Geffen School of Medicine at UCLA, Department of Medicine Section of Endocrinology. Dr Streja received his MD from the Carol Davilla School of Medicine in Bucharest Romania. He trained in internal medicine in Canada and subsequently undertook a fellowship in Endocrinology sponsored by the Ontario Heart Foundation for studies in lipid metabolism. He taught Medicine and Physiology at the University of Manitoba where he was also director of the diabetes clinic. He moved to the United States in 1979 and taught at UCLA since. He is a member of the American Heart Association and of the American Diabetes Association, and he is a fellow of the Royal College of Physicians of Canada and of the American Association of Clinical Endocrinologists. His main scientific interest has been in clinical research, particularly in cardiovascular prevention for patients with diabetes. He has conducted over 150 randomized trials in the field of diabetes and lipids. Dr Streja has authored chapters in five textbooks and co-authored numerous scientific publications. He has lectured in the area of lipids and cardiovascular prevention nationally, in the US, and internationally.

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)0.006
metaresearch head score (Gemma)0.058
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: Editorial
Teacher disagreement score0.215
Threshold uncertainty score0.720

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.058
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.002
Science and technology studies0.0030.001
Scholarly communication0.0080.005
Open science0.0030.003
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.2150.139

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 head0.015
GPT teacher head0.292
Teacher spread0.277 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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