Magnetic resonance imaging-based scoring of the diseased lung in the preterm infant with bronchopulmonary dysplasia: UNiforme Scoring of the disEAsed Lung in BPD (UNSEAL BPD)
Bibliographic record
Abstract
Neonatal chronic lung disease lacks standardized assessment of lung structural changes. We addressed this clinical need by the development of a novel scoring system [UNSEAL BPD (UNiforme Scoring of the disEAsed Lung in BPD)] using T2-weighted single-shot fast-spin-echo sequences from 3 T MRI in very premature infants with and without bronchopulmonary dysplasia (BPD). Quantification of interstitial and airway remodeling, emphysematous changes, and ventilation inhomogeneity was achieved by consensus scoring on a five-point Likert scale. We successfully identified moderate and severe disease by logistic regression [area under the curve (AUC), 0.89] complemented by classification tree analysis revealing gestational age-specific structural changes. We demonstrated substantial interreader reproducibility (weighted Cohen's κ 0.69) and disease specificity (AUC = 0.91). Our novel MRI score enables the standardized assessment of disease-characteristic structural changes in the preterm lung exhibiting significant potential as a quantifiable endpoint in early intervention clinical trials and long-term disease monitoring.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".