Virtual four-dimensional imaging of lung parenchyma by optical coherence tomography in mice
Bibliographic record
Abstract
In this feasibility study, we present a method for virtual 4-D imaging of healthy and injured subpleural lung tissue in the ventilated mouse. We use triggered swept source optical coherence tomography (OCT) with an A-scan frequency of 20 kHz to image murine subpleural alveoli during the inspiratory phase. The data acquisition is gated to the ventilation pressure to take single B-scans in each respiration cycle for different pressure levels. The acquired B-scans are combined off-line into one volume scan for each pressure level. The air fraction in healthy lungs and injured lungs is measured using 2-D OCT en-face images. Upon lung inspiration from 2 to 12 cm H(2)O ventilation pressure, the air fraction increases in healthy lungs by up to 11% and in injured lungs by 8%. This expansion correlates well with results of previous studies, reporting increased alveolar area with increased ventilation pressures. We demonstrate that OCT is a useful tool to investigate alveolar dynamics in spatial dimensions.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".