Single photon emission computed tomography/computed tomography in the evaluation of neuroendocrine tumours
Bibliographic record
Abstract
The scintigraphic investigation of neuroendocrine tumours such as carcinoids has depended on standard techniques such as I-metaiodobenzylguanidine and In-pentetreotide imaging. More recently, the use of PET techniques such as Ga-DOTATATE has been advocated. An alternative improved modality is high-quality single photon emission computed tomography/computed tomography (SPECT/CT), which has the advantages of better sensitivity and specificity and has shown improved localization in up to 60% of cases. These advantages are especially true for pancreatic and lymph node lesions. Overall, SPECT/CT can result in a change in clinical management in 25% of patients. Although it is possible to combine SPECT and CT performed at different time points, there is better anatomical localization and improved reporter confidence when SPECT and CT are performed simultaneously.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".