Establishing Literature-Based Items for an Oral Mucositis Assessment Tool in Children
Bibliographic record
Abstract
Although there are numerous instruments for oral mucositis (OM) assessment in adults, there is a lack of validated instruments for use in children. The objectives of this systematic review were to describe literature-based items that should be considered for a pediatric mucositis scale and other issues that should be considered when assessing mucositis in children. Literature search of PubMed and bibliography searches identified articles relevant to the assessment of mucositis and mucositis assessment studies in children. The elements established from the literature were grouped under objective, subjective, and functional items. Other issues that require consideration include the conditions for the assessment of the oral cavity and the etiology of OM. The resultant list included 23 items that have been used in mucositis assessment scales. This list of items may be used as an initial step in developing a new pediatric OM scale that particularly focuses on the unique issues in children.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".