Bibliographic record
Abstract
Introduction and Objectives:Historically pheochromocytoma excision has proven to be challenging for a variety of reasons such as blood pressure spikes and blood loss.With the development of sophisticated robotic systems, this surgery has become more feasible.The following will present a case highlighting the excision of a metabolically active pheochromocytoma using the DaVinci robot.A 79-year-old male presented for evaluation of left adrendal mass measuring 8.0 cm.Subsequent testing revealed pheochromocytoma.Methods: Preoperatively the patient received a two week alpha blockade.The DaVinci robot was side docked with left side elevated.It was noted that manipulation of the tumour resulted in a spike of the patient's blood pressure.Patient was noted to have large accessory veins, controlled with 45 mm Ethicon endoscopic vascular stapler.Following occlusion of the veins there was a noted drop in blood pressure, typical of metabolically active pheochromocytoma.Blood loss was estimated at 200 cc.Procedure was tolerated well.Results: Pheochromocytoma was successfully removed assistance from the DaVinci Robot.Minimal blood loss was encountered and complications were minimal.Patient developed postoperative ileus and was discharged home on postoperative day 16.Conclusion: Robotic assistance allowed for limited manipulation of the lesion, reducing the risk of unsafe blood pressure spikes.Blood loss was minimized with the use of the Ethicon endoscopic vascular stapler.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.459 | 0.135 |
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".