A novel tool in laryngeal surgery: Preliminary results of the picosecond infrared laser
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Conventional lasers ablate tissue through photothermal, photomechanical, and/or photoionizing effects, which may result in collateral tissue damage. The novel nonionizing picosecond infrared laser (PIRL) selectively energizes tissue water molecules using ultrafast pulses to drive ablation on timescales faster than energy transport to minimize collateral damage to adjacent cells. STUDY DESIGN: Animal cadaver study. METHODS: Cuts in porcine laryngeal epithelium, lamina propria, and cartilage were made using PIRL and carbon dioxide (CO₂) laser. Lateral damage zones and cutting gaps were histologically compared. RESULTS: The mean widths of epithelial (8.5 μm), subepithelial (10.9 μm), and cartilage damage zones (8.1 μm) were significantly lower for cuts made by PIRL compared with CO₂ laser (p < 0.001). Mean cutting gaps in vocal fold (174.7 μm) and epiglottic cartilage (56.3 μm) were significantly narrower for cuts made by PIRL compared with CO₂ laser (P < 0.01, P < 0.05). CONCLUSION: PIRL ablation demonstrates superiority over CO₂ laser in cutting precision with less collateral tissue damage.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".