Notice bibliographique
Résumé
Current Opinion in Nephrology and Hypertension was launched in 1992. 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 nephrology and hypertension is divided into 12 sections that are each 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 Editors for this issue. SECTION EDITORS Agnes B. FogoAgnes B. FogoProfessor Agnes Borge Fogo completed her medical training at Vanderbilt University Medical School, USA. She has remained at Vanderbilt for residency in pathology and for further training in renal pathology, with the late Dr Alan Glick, and also working in experimental renal diseases, with Dr Iekuni Ichikawa. Her main research interests are focused on progression of chronic kidney disease and the renin angiotensin aldosterone system and its link to the fibrinolytic/thrombolytic plasmin/plasminogen activator system. In recent years, she has explored the possibility of regression of sclerosis, pursued by funding from NIH and other sources. She is also dedicated to diagnostic renal pathology, and has created an online Atlas of Renal Pathology with the American Journal of Kidney Disease and the National Kidney Foundation. Prof. Fogo enjoys being involved with teaching renal pathology, and received the Robert G. Narins award from the ASN in 2011 for her contributions in teaching. She is currently the John L. Shapiro Professor of Pathology, Microbiology and Immunology, Professor of Medicine and Pediatrics and Director of the Renal/Electron Microscopy Laboratory, at Vanderbilt University Medical Center. Navdeep TangriNavdeep TangriDr Navdeep Tangri is an attending physician and Assistant Professor in the Division of Nephrology, Department of Medicine at Seven Oaks General Hospital, University of Manitoba, Canada. Dr Tangri is also an Assistant Professor in the Department of Community Health Sciences at the University of Manitoba, and Adjunct Assistant Professor at Tufts University, USA. Dr Tangri's research program is clinical and translational and focused on improving clinical decision making for patients with advanced chronic kidney disease. He developed and validated the Kidney Failure Risk Equation to predict the need for dialysis in patients with CKD, and is presently engaged in multiple validation and implementation exercises to increase the uptake of the KFRE. In addition, Dr Tangri is conducting a large prospective study on frailty, physical and cognitive function in advanced CKD, as well as comparative effectiveness studies on the safety and effectiveness of medical therapies in this population. He has published over 60 manuscripts and presented at multiple national and international scientific meetings. Dr Tangri currently reviews manuscripts for several major medical journals, including the Annals of Internal Medicine, the Journal of American Society of Nephrology, and the American Journal of Kidney Disease. He sits of the editorial board of the Canadian Journal of Kidney Health and Disease and is Section Editor of Current Opinion in Nephrology and Hypertension. He has active grants from the Canadian Institute of Health Research, the Kidney Foundation of Canada and the Manitoba Health Research Council. In addition, he is a member of numerous associations, including the American Society of Nephrology, a member of the scientific committee of the Canadian Society of Nephrology, and the International Society of Nephrology. Dr Tangri received his medical degree from the University of Manitoba, Winnipeg, Manitoba Canada. He completed his residency program in internal medicine at McGill University, Montreal, Quebec, Canada, and completed his nephrology training and doctoral degree at Tufts Medical Center, Tufts University, in Boston, Massachusetts, USA. He then moved to the University of Manitoba where he has been a full time faculty member since 2011.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,045 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,005 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,008 | 0,004 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,217 | 0,138 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».