Bibliographic record
Abstract
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 fellowship in renal pathology and experimental kidney disease models. Her main research interests are focused on potential regression of chronic kidney disease and tubular-glomerular crosstalk in this process, pursued with funding from the National Institutes of Health 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. She has also authored two books on renal pathology. Prof. Fogo enjoys teaching renal pathology and received the Robert G. Narins award from the American Society of Nephrology in 2011 as well as the Roscoe R. Robinson award from the International Society of Nephrology in 2019, for her contributions in teaching. She is currently President of the ISN and the John L. Shapiro Professor of Pathology, Microbiology and Immunology, Professor of Medicine and Paediatrics and Director of the Renal/Electron Microscopy Laboratory at Vanderbilt University Medical Center, Nashville, Tennessee, USA. Navdeep TangriNavdeep TangriDr Tangri is an attending physician and Professor in the Division of Nephrology, Department of Internal Medicine, and the Rady Faculty of Community Health Sciences at the University of Manitoba, Winnipeg, Canada. Dr Tangri's research program is clinical, 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 leading a multinational randomized trial on the safety and efficacy of a new therapy in this population. He has published over 300 manuscripts, presented at multiple national and international scientific meetings, and is a recipient of the CIHR New Investigator Award and a CIHR Foundation grant.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.219 | 0.141 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".