Bibliographic record
Abstract
Bronchiolar pathologic lesions result from the interplay between inflammatory and mesenchymal cells following injury to bronchioles. Offending agents include viruses, bacteria, fungi, cigarette smoke, toxic inhalants, inorganic dusts, allergens, and systemic or localized autoimmune or inflammatory processes. Bronchiolar pathologic lesions also arise in the context of allograft transplantation and pathology of the large airways and in the setting of an idiopathic disorder. Given the great variety of sources of injury and diversity of clinical, radiological, and functional patterns that result, it is no surprise that most morphological abnormalities of the bronchioles are not specific. They thus represent a diagnostic challenge to the surgical pathologist, and the necessity of a multidisciplinary (clinical/radiological/pathologic) approach cannot be overemphasized. After a survey of the normal histology of bronchioles, we present a pragmatic classification that reflects the spectrum of bronchiolar pathology, illustrating the intimate interdependence of clinical, radiological, and pathologic findings in assessing the significance of bronchiolar lesions. This classification is intended to be applicable to surgical pathology material that can be correlated with clinical disease syndromes. It includes asthma-associated bronchiolar changes, chronic bronchitis/emphysema-associated bronchiolar changes, cellular bronchiolitis, respiratory bronchiolitis, bronchiolitis obliterans with intraluminal polyps/ BOOP, constrictive bronchiolitis, mineral dust small airway disease, peribronchiolar fibrosis and bronchiolar metaplasia, and bronchiolocentric nodules.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".