High-resolution computed tomographic characteristics in acute farmer's lung and in its follow-up
Bibliographic record
Abstract
High resolution computed tomography (HRCT) scans are increasingly used in hypersensitivity pneumonitis (HP). This study looked at HRCT findings at different phases of farmer's lung (FL), a common form of HP. A cross sectional analysis of 95 HRCT scans of FL cases (20 acute, 75 with a history of FL, 48 still in contact (Ex +) (dairy farm), and 27 who had ceased contact (Ex-)) was made. All scans were read independently by two, and if needed by three, radiologists blinded to the category. The lungs were divided into six regions (fives lobes + lingula), and read for attenuation/mosaic, ground-glass, micronodules, fibrosis, and emphysema. A score of 0-3 was given for each region and each variable: 0 = absence, 1 =<25% of the surface, 2 = 25-50%, 3 =>50%. Mediastinal lymphadenopathy was also noted. Ground glass, predominating in the lower lobes, was the most frequent feature in the acute and Ex+ cases. Other abnormalities had no preferential distribution. Ex+ had more ground-glass than the Ex- (p=0.0025). Emphysema was more frequently seen than interstitial fibrosis (p=0.004). Mediastinal lymphadenopathy was present in 26 cases (9 acute, 10 Ex+ and 7 Ex-). In conclusion, in farmer's lung: 1) ground-glass predominates in the lower lobes while the other abnormalities have no anatomic predilection; 2) contact avoidance allows a better resolution of computed tomography abnormalities than continued exposure; 3) emphysema is a more frequent finding than interstitial fibrosis; and 4) the presence of mediastinal lymphadenopathy has no negative diagnostic value.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".