Computed Tomographic Features of Primary Small Cell Neuroendocrine Tumors of the Gallbladder
Bibliographic record
Abstract
PURPOSE: This study aimed to report the computed tomography (CT) imaging features of primary small cell neuroendocrine tumors of the gallbladder (PSCNETGs). MATERIALS AND METHODS: The CT examinations of 9 patients (5 women, 4 men; median age, 57 years) with histopathologically proven PSCNETG were reviewed. Computed tomographic images were analyzed with respect to morphologic features of primary tumors and accompanying lymph nodes. RESULTS: All PSCNETGs were visible on CT, with a median largest axial diameter of 60 mm (Q1, 30 mm; Q3 mm, 82; range, 25-86 mm). These tumors presented with extraluminal growth (8/9; 89%), heterogeneous enhancement (8/9; 89%), gallbladder replacement greater than 50% (5/9; 56%), hepatic metastases (5/9; 56%), and direct liver involvement by tumor (4/9; 44%). Enlarged lymph nodes were present in all patients (9/9; 100%) with a median largest axial diameter of 39 mm (Q1, 23 mm; Q3, 48 mm; range, 12-62 mm). Vessel encasement by lymph nodes was present in 6 (67%) of 9 patients. CONCLUSION: Primary small cell neuroendocrine tumors of the gallbladder predominantly presents as a large, heterogeneous gallbladder mass with extraluminal growth in association with large metastatic lymph nodes and intrahepatic metastases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".