Theranostic Imaging Surrogates for Targeted Alpha Therapy: Progress in Production, Purification, and Applications
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
This article highlights recent developments of SPECT and PET diagnostic imaging surrogates for targeted alpha particle therapy (TAT) radiopharmaceuticals. It outlines the rationale for using imaging surrogates to improve diagnostic-scan accuracy and facilitate research, and the properties an imaging-surrogate candidate should possess. It evaluates the strengths and limitations of each potential imaging surrogate. Thirteen surrogates for TAT are explored: 133La, 132La, 134Ce/134La, and 226Ac for 225Ac TAT; 203Pb for 212Pb TAT; 131Ba for 223Ra and 224Ra TAT; 123I, 124I, 131I and 209At for 211At TAT; 134Ce/134La for 227Th TAT; and 155Tb and 152Tb for 149Tb TAT.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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