Development of a capsule endoscopy scoring index for small bowel mucosal inflammatory change
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
BACKGROUND: Capsule endoscopy can identify small bowel mucosal inflammatory change. However, there has been no validated index for capsule endoscopy findings. This manuscript documents the development of such an index. AIM: To develop a capsule endoscopy scoring index for small bowel mucosal inflammatory change. METHODS: The index was created in four separate steps. First, parameters and descriptors of inflammatory change were identified. Secondly, blinded readers prospectively graded the presence or absence of each parameter on de-identified videos and graded a perceived global assessment of overall severity. Thirdly, the individual parameters and descriptors were ranked in order of severity. Fourthly, values for each parameter were created using the descent gradient methodology. The premise was to assure that the final numerical score reflected the global assessment and that the global assessment agreed with the ranking of finding severity. Results were compiled for the three categories: no or clinically insignificant change, mild change, and moderate or severe change. Thresholds were determined. RESULTS: The final index includes three parameters: villous oedema, ulcer and stenosis. A score <135 is designated normal or clinically insignificant mucosal inflammatory change, a score between 135 and 790 is mild, and a score > or = 790 is moderate to severe. CONCLUSION: This capsule endoscopy score provides a common language to quantify small bowel inflammatory changes.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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 it