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
There is a very large number of experimental approaches that prevent cigarette smoke-induced emphysema in laboratory animals, but the few similar treatments that have been tried in humans have had minimal effects, leading to questions of whether animal models of chronic obstructive pulmonary disease (COPD) are of any use in developing treatments for human disease. We review possible reasons for this problem. First, humans usually get treated when they have severe (Global Initiative for Chronic Obstructive Lung Disease III/IV) COPD, but animal models only produce mild (Global Initiative for Chronic Obstructive Lung Disease I/II) disease that never progresses after smoking cessation, and never develops spontaneous exacerbations (i.e., animal models are not models of severe human disease, and probably can't be used to model treatment of severe disease). Second, animal models have concentrated on emphysema and largely ignored small airway remodeling, but small airway remodeling is an equally important cause of airflow obstruction. In addition, small airway remodeling and emphysema are independent responses to smoke, and some experimental animal treatments prevent both lesions, but many do not. Third, animal models are typically Day 1 of smoke exposure "prevention" models, but humans are always treated well along in the course of their disease; thus, any human treatment will be an intervention, and not a prevention. We propose that animal models should examine both emphysema and small airway remodeling, and that experiments should include a relatively late intervention arm. This approach, combined with the realization that human COPD probably needs early rather than late treatment, may make development of treatments based on animal models more relevant.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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