The development and evaluation of the pain indicator for communicatively impaired children (PICIC)
Bibliographic record
Abstract
A previous study found that parents of communicatively impaired children with severe cognitive impairments identified six core cues as indicating definite or severe pain in their child (J. Pediatr. Psychol. 27 (2002) 209). The frequency of each cue was assessed by 67 caregivers of communicatively impaired children, twice per day over a 1 week period. On each occasion the caregivers also rated whether they considered their child to be in pain and the severity of any pain. There was a statistically significant relationship between five of the cues and the presence and severity of pain. The single cue of screwed up or distressed looking face was the strongest predictor and on its own correctly classified 87% of pain and non-pain episodes. The study highlights the potential clinical utility of a short carer completed assessment to assess pain in this vulnerable group of 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 | 0.024 | 0.004 |
| 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 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".