MORPHOLOGICAL ANALGYSIS OF BIPOLAR RADIOFREQUENCY THERMOSET PRODUCED BY DIFFERENT GAUGE RADIONICS CANNULAE
Bibliographic record
Abstract
Objective:Compared with monopolar radiofrequency (RF), bipolar RF thermocoagulation has been generally accepted to be a better treatment for patients with sacroiliac joint dysfunction, discogenic pain et al. In the precondition of forming continuous strip thermoset, the larger distance between two probes, the more related patients could be benefit from it. Our objective is to analyze the relationship between gauge of radionics cannulae and thermoset morphology. Methods: Egg white was used as the protein medium. Pairs of 22 gauge (G), 21G and 20G Baylis radionics cannulae with the same active tip (5mm) were used, secured in a parallel position 2, 4, 6, 8, 10, 12, 14, 16 mm apart and submerged in egg white. 90℃180 seconds radiofrequency thermocoagulation was repeated 5 times. The progress of thermoset formation was photographed and analyzed. Results: In the same experimental condition, continuous strip thermoset of 22G, 21G and 20G radionics cannulae were formed, when the cannulae were spaced 8mm, 12mm and 14mm correspondingly, the maxim thermoset area of each group was 88.70 mm2, 118.15 mm2 and 135.00 mm2 respectively. As the distance between two probes increased, final distance of continuous strip thermoset of 22G, 21G and 20G increased proportionally, but final height and maximal outside cannulae thermoset distances did not increased. Conclusions: With the same active tips, bipolar RF does create a continuous strip thermoset that is proportional in size to the diameter of the cannulae. When the distance increased, the thermoset area can be increased by augmenting RF time until the maximum reached, but maximal outside cannulae thermoset distance does not increased respectively.
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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 | 0.000 | 0.000 |
| 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".