Accurate measures of changes in regional lung air volumes from chest x-rays of small animals
Bibliographic record
Abstract
Abstract Objective . To develop a robust technique for calculating regional volume changes within the lung from x-ray radiograph sequences captured during ventilation, without the use of computed tomography (CT). Approach . This technique is based on the change in transmitted x-ray intensity that occurs for each lung region as air displaces the attenuating lung tissue. Main results . Lung air volumes calculated from x-ray intensity changes showed a strong correlation ( R 2 = 0.98) against the true volumes, measured from high-resolution CT. This correlation enables us to accurately convert projected intensity data into relative changes in lung air volume. We have applied this technique to measure changes in regional lung volumes from x-ray image sequences of mechanically ventilated, recently-deceased newborn rabbits, without the use of CT. Significance . This method is suitable for biomedical research studies,enabling quantitative regional measurement of relative lung air volumes at high temporal resolution, and shows great potential for future clinical application.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".