Clinical Diagnosis of Hypersensitivity Pneumonitis
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
The diagnosis of hypersensitivity pneumonitis (HP) is difficult and often relies on histopathology. Our objective was to identify diagnostic criteria and to develop a clinical prediction rule for this disease. Consecutive patients presenting a condition for which HP was considered in the differential diagnosis underwent a program of simple standardized diagnostic procedures. High-resolution computed tomography scan and bronchoalveolar lavage (BAL) defined the presence or absence of HP. Patients underwent surgical lung biopsy when the computed tomography scan, BAL, and other diagnostic procedures failed to yield a diagnosis. A cohort of 400 patients (116 with HP, 284 control subjects) provided data for the rule derivation. Six significant predictors of HP were identified: (1) exposure to a known offending antigen, (2) positive precipitating antibodies to the offending antigen, (3) recurrent episodes of symptoms, (4) inspiratory crackles on physical examination, (5) symptoms occurring 4 to 8 hours after exposure, (6) and weight loss. The area under the receiver operating characteristic curve was 0.93 (95% confidence interval: 0.90-0.95). The rule retained its accuracy when validated in a separate cohort of 261 patients. The diagnosis of HP can often be made or rejected with confidence, especially in areas of high or low prevalence, respectively, without BAL or biopsy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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