Reliability of classification of cerebral palsy in low-birthweight children in four countries
Bibliographic record
Abstract
The reliability of classification of cerebral palsy (CP) in low-birthweight children was assessed by using clinical and research study records sampled from population-based cohort studies in the USA, The Netherlands, Canada, and Germany. Records of neurological examination findings and functional motor assessments were submitted to up to five pediatricians with expertise in CP diagnosis, who grouped children into categories referred to as 'disabling' CP, 'non-disabling' CP, and no CP. Each study provided between 31 and 51 records of children assessed between 2 and 8 years of age, approximately equally divided among the three groupings. The discrimination between 'any CP' and 'no CP' was only fair (mean Kappa coefficients 0.37 to 0.69). However, when more detailed information describing motor function was used, children with 'disabling' CP could be distinguished, on the basis of records, from those without CP or with 'non-disabling' CP with good to excellent reliability (mean Kappa coefficients 0.69 to 0.88). Because of the substantially higher agreement observed when these functional distinctions are made, we recommend that reports or comparisons of rates of CP should include levels of motor function of children with CP, and not simply total CP, among the outcomes of interest.
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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 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 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".