Pathologic Subgroups of Nonspecific Interstitial Pneumonia
Bibliographic record
Abstract
OBJECTIVE: To determine whether the subtypes of nonspecific interstitial pneumonia (NSIP) could be differentiated from other idiopathic interstitial pneumonias (IIPs) on the basis of findings on high-resolution computed tomography (CT). METHODS: Two observers evaluated the high-resolution CT findings in 90 patients with IIPs. The patients included 36 with NSIP, 11 with usual interstitial pneumonia (UIP), 8 with cryptogenic organizing pneumonia (COP), 10 with acute interstitial pneumonia (AIP), 14 with desquamative interstitial pneumonia (DIP) or respiratory bronchiolitis-associated interstitial lung disease (RB-ILD), and 11 with lymphoid interstitial pneumonia (LIP). The NSIP cases were subdivided into group 1 NSIP (n = 6), group 2 NSIP (n = 15), and group 3 NSIP (n = 15). RESULTS: Observers made a correct diagnosis with a high level of confidence in 65% of NSIP cases, 91% of UIP cases, 44% of COP cases, 40% of AIP cases, 32% of DIP or RB-ILD cases, and 82% of LIP cases. Group 1 NSIP was misdiagnosed as AIP, DIP or RB-ILD, and LIP in 8.3% of patients, respectively. Group 2 NSIP was misdiagnosed as COP in 10% of patients, LIP in 6.7%, AIP in 3.3%, and DIP or RB-ILD in 3.3%. Group 3 NSIP was misdiagnosed as UIP in 6.7% of patients, COP in 6.7%, and DIP or RB-ILD in 3.3%. CONCLUSIONS: In most patients, NSIP can be distinguished from other IIPs based on the findings on high-resolution CT. Only a small percentage of patients with predominantly fibrotic NSIP (group 3 NSIP) show overlap with the high-resolution CT findings of UIP.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".