Bibliographic record
Abstract
Conventional two-dimensional and three-dimensional single photon emission computed tomography and positron emission tomography imaging tools and specific inhaled radiotracers allow accurate and reliable measurements of drug delivery to the lung. Pharmacokinetics and patterns of drug distribution can be monitored over time. In addition, physiologic measurements of ventilation, perfusion, mucociliary clearance, inflammation, and respiratory absorption can be determined using imaging; the results correlate with "black-box" outcomes (for example, spirometry, airway responsiveness, and inflammatory markers in sputum, and bronchoalveolar lavage fluid), providing an indication of the disease state in situ and the effectiveness of therapeutic and other interventions on these critical lung functions. Imaging is widely used in drug discovery. Screening of new drugs using animal models and specifically molecular imaging before human studies is an approach used extensively by the pharmaceutical industry. Topical drug delivery to the lung remains the route of choice for administering respiratory therapies; recently, inhaled therapies have been formulated to gain access to the systemic circulation via the distal lung. Imaging provides a means of validating drug delivery to the site of action in the lung and of measuring the resulting pharmacokinetics of these therapies. No other tool or test provides this type of visual detail supported by numerical information related to a specific drug molecule.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 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 | 0.004 |
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".