Bibliographic record
Abstract
Molecular imaging represents tissue-specific imaging and quantification of physiologic (functional) and molecular events in tumors utilizing new noninvasive imaging modalities, radioligands, and contrast agents. It combines anatomic, physiologic, and metabolic information in a single imaging session. Molecular imaging relies on the ability to target genes and proteins that are linked directly or indirectly to human disease. New imaging biomarkers are being developed. In addition, functional and molecular imaging can potentially replace anatomic longitudinal studies by assessing treatment response earlier. Vascular targeting agents can be evaluated by imaging of tumor angiogenesis using magnetic resonance imaging (MRI), computed tomography and ultrasound, and positron emission tomography (PET). Targeted contrast agents can accomplish site-directed imaging or therapy by a variety of active and passive mechanisms. Furthermore, there is the possibility of combining different modalities such as ultrasonic imaging and MRI or MRI and PET to increase the flexibility unachievable with either modality alone. However, there is a need to standardize these techniques so that longitudinal evaluation of tumor response to treatment is feasible.
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 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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".