Concurrent validity of the Neurobehavioural Assessment for Pre-term Infants (NAPI) at term age
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Accurate measurement of neonatal neurological integrity is critical for early identification of pre-term and full-term infants at-risk for developmental disability. The Neurobehavioural Assessment for Pre-term Infants (NAPI) was developed to measure the progression of neurobehavioural development in pre-term infants born between 32 weeks post-conceptional age (PCA) and term. This instrument has many unique advantages; however, criterion validity is unknown and results are subsequently difficult to interpret. OBJECTIVES: This study examined the concurrent validity of the NAPI against a criterion instrument, the Einstein Neonatal Neurobehavioural Assessment Scale (ENNAS), which measures similar constructs and has demonstrated excellent reliability and validity. METHODS: A sample of 41 pre-term and full-term infants (40 +/- 2 weeks) was assessed with the NAPI and ENNAS on the same day. RESULTS: The findings demonstrated that correlations between similar NAPI clusters and ENNAS clusters ranged from 0.35-0.65 and correlations between many similar individual NAPI and ENNAS items ranged from 0.40-0.60. Two NAPI clusters also discriminated between normal, abnormal and suspect performance on the ENNAS. CONCLUSION: The NAPI has many unique advantages as a tool. It examines neonates serially, has established weekly normative data and requires minimal infant handling. This study provides new validation of the NAPI instrument.
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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 | 0.000 | 0.000 |
| 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 it