Reliability and Initial Validation of the Ulcerative Colitis Endoscopic Index of Severity
Bibliographic record
Abstract
BACKGROUND & AIMS: We studied the reliability of the previously described Ulcerative Colitis Endoscopic Index of Severity (UCEIS) and validated it with an independent cohort of investigators. METHODS: We created a new library of 57 videos of flexible sigmoidoscopy and stratified them based on disease severity. Twenty-five investigators were each randomly assigned to assess 28 videos (which included 4 duplicates to assess intraobserver reliability). Investigators were blinded to clinical details except for 2 of 4 duplicated videos (to assess the impact of knowledge of symptoms on assessment). Three descriptors ("vascular pattern", "bleeding", and "erosions and ulcers") comprising the UCEIS were scored with a visual analogue scale (VAS) to assess overall severity. Intrainvestigator and interinvestigator agreement was characterized by κ statistical analysis; reliability ratios were used to compare VAS and UCEIS scores. RESULTS: There was a high level of correlation between UCEIS scores and overall assessment of severity (correlation coefficient, 0.93). Internal consistency (Cronbach α analysis) was 0.86. Intrainvestigator and interinvestigator reliability ratios for UCEIS scores were 0.96 and 0.88, respectively. Intrainvestigator agreement in determination of the UCEIS score was good (κ = 0.72), with individual descriptors ranging from a κ of 0.47 (for bleeding) to 0.87 (for vascular pattern). Interinvestigator agreement in determination of UCEIS scores was moderate (κ = 0.50), with descriptors ranging from a κ of 0.48 (for bleeding) to 0.54 (for vascular pattern). Intrainvestigator variability in determining UCEIS scores did not change appreciably when a video was presented with clinical details. CONCLUSIONS: The UCEIS and its components show satisfactory intrainvestigator and interinvestigator reliability. Among investigators, the UCEIS accounted for a median of 86% of the variability in evaluation of overall severity on the VAS when assessing the endoscopic severity of UC and was unaffected by knowledge of clinical details.
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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 | 0.036 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".