Tomographic Comparison of Ventilation Techniques for CT-Guided Thoracoscopic Staple Excision of Subcentimeter Lung Nodules
Bibliographic record
Abstract
This study was planned to compare the computed tomographic detectability of lung nodules in three ventilatory conditions: total lung capacity, high-frequency ventilation, and total lung deflation. In an ex vivo lung model, 44 nodules were simulated. Using computed tomography (CT) scans, nodules were detected and compared to the actual number and excised under CT guidance. Simulated nodules measured 6.2 +/- 2.1 mm and demonstrated an attenuation of 175 +/- 14 HU. Observer confidence was highest at total lung capacity (5.00 +/- 0.00), in comparison to high-frequency ventilation and total lung deflation (4.69 +/- 0.78, 4.94 +/- 0.27, p = .24). The kappa score for total lung capacity, high-frequency ventilation, and total lung deflation was 1.00, 0.96, and 0.98, respectively, indicating a very high interrater reliability. Although surgical devices generated a substantial artifact, 90% of nodules were excised. Thus, although total lung capacity produces the highest confidence level, all three of the ventilatory techniques examined have similar detection of subcentimeter pulmonary nodules using computed tomography scans.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".