Development of a Tissue Oxygen Saturation Detection System for Improving Surgical Training
Bibliographic record
Abstract
Delicate tissue encountered in surgery is prone to ischemic damage from grasping and retracting especially by novice surgeons. Currently, there are no existing techniques to quantitatively assess tissue health during surgical maneuver. A transmission and reflectance mode tissue oxygenation (StO2) sensor was developed and integrated into a standard laparoscopic tool and custom forceps to continuously measure tissue oxygenation during surgery. Numerous wavelengths including 470nm, 500nm, 510nm, 560nm, 570nm, 586nm, 660nm and 940nm were tested in reflection mode while 660nm and 940nm were tested in transmission mode. StO2 sensor successfully detected oxygenation changes on the finger and during ex vivo experiment conducted on arterial and venous blood samples. StO2 sensor was unable to monitor changes when grasping small intestine and liver using surgical instruments. Various factors including lack of hemoglobin at the site of measurement, tissue thickness changes during grasps, and motion artifacts limited the use of this technology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".