The Cow’s Milk-Related Symptom Score (CoMiSSTM): Health Care Professional and Parent and Day-to-Day Variability
Bibliographic record
Abstract
The Cow’s Milk-related Symptom Score (CoMiSSTM) was created as an awareness tool for cow’s milk allergy. The aim of the present study was to analyze the inter-rater variability between a pediatrician, parents, and day to day variability. A Health Care Professional (HCP) and parent filled in the CoMiSS independently and blinded for each other to evaluate inter-rater variability. In order to validate day-to-day variability, a parent filled in the CoMiSS during 3 consecutive days and was compared to the CoMiSS scored by the HCP. The absolute agreement between parent and HCP was 75%, and 92.6% and 100% with a tolerance of 0, 1, and 2 points, respectively, resulting in excellent agreement with an intraclass correlation coefficient (ICC) 0.981 (95% Confidence Interval 0.974–0.986, p < 0.001). Day-to-day variability during 3 consecutive days resulted in an absolute agreement of 30%, increasing to 80% and 88.6% when 2 and 3 points, respectively, were accepted. The ICC was excellent for the parental prospective scores (0.93, 95% CI 0.90–0.96; p < 0.001). Day-to-day variability indicates that CoMiSS has a moderate inter-rater reliability. A very low variability was observed when scored prospectively over three days. Data suggest that the CoMiSS can reliably be scored by parents without additional training.
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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 | 0.026 |
| 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 | 0.001 |
| 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".