Review of the Clinical and Technical Aspects of<sup>99m</sup>Tc-Dimercaptosuccinic Acid Renal Imaging: The Comeback “Kit”
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
<sup>99m</sup>Tc-labeled dimercaptosuccinic acid (<sup>99m</sup>Tc-DMSA) imaging is a well-established and highly sensitive method for the diagnosis of several renal cortical disorders affecting children and adults. Beginning in 2014, <sup>99m</sup>Tc-DMSA availability was severely impaired when it was added to the Drug Shortages List of the U.S. Food and Drug Administration and was commercially unavailable thereafter. The agent shortage negatively impacted practitioners’ ability to evaluate renal cortical defects in children and adults and changed renal imaging practice. A survey among pediatric nuclear medicine clinicians confirmed the clinical need for <sup>99m</sup>Tc-DMSA. Finally, in early 2023 the Food and Drug Administration again approved <sup>99m</sup>Tc-DMSA in the United States. During the <sup>99m</sup>Tc-DMSA shortage, established practitioners may not have had the opportunity of using <sup>99m</sup>Tc-DMSA as they were accustomed in their experience. Also, newer imaging specialists and referring physicians and technologists may not have benefited from having <sup>99m</sup>Tc-DMSA in their training. Therefore, it is time to bring back <sup>99m</sup>Tc-DMSA into the armamentarium of imaging methods available to evaluate regional cortical renal function.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| 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