Determination of optimal location for thoracoscopic-assisted pulmonary surgery for lung lobectomy in cats
Bibliographic record
Abstract
OBJECTIVE: To determine the optimal intercostal space (ICS) for thoracoscopic-assisted pulmonary surgery for lung lobectomy in cats. SAMPLE: 8 cat cadavers. PROCEDURES: Cadavers were placed in lateral recumbency. A 5-cm minithoracotomy incision was made in the middle third of ICS 4 through 7 on the left side and 4 through 8 on the right side, and a wound retractor device was placed. A camera port was made in the middle third of ICS 9. Each lung lobe was sequentially exteriorized at each respective ICS. A thoracoabdominal stapler was placed to simulate a lung lobectomy, and distance from the stapler anvil to the hilus was measured. RESULTS: For the left cranial lung lobe, there was no significant difference in median distance from the stapler anvil to the pulmonary hilus for ICS 4 through 6. Simulated lobectomy of the left caudal lung lobe performed at ICS 5 and 6 resulted in a significantly shorter distance, compared with lobectomy performed at ICS 4 and 7. Simulated lobectomy of the right cranial and right middle lung lobes performed at ICS 4 and 5 resulted in a significantly shorter distance, compared with lobectomy performed at ICS 7. Simulated lobectomy of the accessory and right caudal lung lobes at ICS 5 and 6 resulted in a significantly shorter distance than for lobectomy performed at ICS 8. CONCLUSIONS AND CLINICAL RELEVANCE: An optimal ICS for a minithoracotomy incision was determined for thoracoscopic-assisted lung lobectomy in cats.
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How this classification was reachedexpand
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".