Structure and Function Relationships in Diseases of the Small Airways
Bibliographic record
Abstract
It is well known that particulate matter suspended in the earth's atmosphere generated by tobacco smoke, automobile exhaust, industrial processes, and forest fires has been identified as a major risk factor for chronic lung disease. Particulate matter can be divided into large, intermediate, and fine particulates. When inhaled, large particulates develop sufficient momentum to leave the flowing stream of inhaled air and deposit by impaction in the nose, mouth, nasopharynx, larynx, trachea, and central bronchi. Intermediate-sized particulates that develop less momentum deposit in the smaller bronchi and larger bronchioles, and the finest particulates that develop the least momentum make it to the distal gas-exchanging tissue, where gas moves solely by diffusion. On the basis of Einstein's classic work on Brownian motion that showed particles suspended in a gas diffuse much more slowly than the gas in which they are suspended, we postulate that the small airways that accommodate the shift from bulk airflow to diffusion become the major site for deposition of fine particles, resulting in a host immune response. Much remains to be learned about the interaction between the deposition of fine particulates and the host immune and tissue responses; the purpose of this review is to examine the hypothesis that the smallest conducting airways and proximal gas-exchanging tissue are the primary sites for the deposition of the finest particulates inhaled into the lungs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".