Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Emerging evidence linking gadolinium-based contrast agents (GBCAs) to nephrogenic systemic fibrosis (NSF) has changed medical practice patterns toward forgoing GBCA-enhanced magnetic resonance imaging (MRI) or substituting other imaging methods, which are potentially less accurate and often radiation-based. This shift has been based on reports of high NSF incidence at sites where a confluence of risk factors occurred in patients with severe renal dysfunction. This review article explores the factors that affect NSF risk, compares risks of alternative imaging procedures, and demonstrates how risk can be managed by careful selection of GBCA dose, timing of injection with respect to dialysis, and other factors. Nearly half of NSF cases are a milder form that does not cause contractures or reduce mobility. It appears that eliminating even a single risk factor can reduce NSF incidence/risk at least 10-fold. Elimination of multiple risk factors by using single-dose GBCA, dialyzing dialysis patients quickly following GBCA administration, avoiding GBCA in acute renal failure while serum creatinine is rising, and avoiding nonionic linear GBCA in renal failure patients may reduce NSF risk more than a thousand-fold, thereby allowing safe GBCA-enhanced MRI in virtually all patients. J. Magn. Reson. Imaging 2009;30:1298-1308. (c) 2009 Wiley-Liss, Inc.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it