Validation of healthcare professional proxy‐reported children’s International Mucositis Evaluation Scale
Bibliographic record
Abstract
OBJECTIVE: The objective was to describe the reliability and validity of the healthcare professional proxy-report version of the Children's International Mucositis Evaluation Scale (ChIMES). METHODS: We included pediatric patients who were between 4 and 21 years of age and scheduled to undergo hematopoietic cell transplantation. Mucositis was evaluated by trained healthcare professionals who scored ChIMES, the World Health Organization oral toxicity scale, mouth, and throat pain visual analogue scale, National Cancer Institute-Common Terminology Criteria and the Oral Mucositis Daily Questionnaire. Measures were completed daily and evaluated on days 7-17 post-stem cell infusion for this analysis. Psychometric properties examined were internal consistency, test-retest reliability (days 13 and 14), and convergent construct validity. RESULTS: There were 192 participants included. Cronbach's alpha was 0.90 for ChIMES Total Score and 0.93 for ChIMES Percentage Score. Test-retest reliability were as follows: intraclass correlation coefficient (ICC) 0.82 (95% confidence interval (CI) 0.77-0.85) for ChIMES Total Score and ICC 0.82 (95% CI 0.77-0.86) for ChIMES Percentage Score. In terms of construct validation, all correlations between measures met or exceeded those hypothesized (all p < 0.05). CONCLUSIONS: The healthcare professional proxy-report version of ChIMES is reliable and valid for children and adolescents undergoing hematopoietic cell transplantation.
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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 | 0.014 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".