Feasibility and efficacy of ultrasonographic and laparoscopic guidance for microwave ablation of clinically normal canine ovaries
Bibliographic record
Abstract
OBJECTIVE: To determine the optimal energy profile for and to assess the feasibility and efficacy of ultrasonographic and laparoscopic guidance for microwave ablation (MWA) of clinically normal canine ovaries. SAMPLE: 44 extirpated ovaries from 22 healthy dogs. PROCEDURES: In the first of 2 trials, 13 dogs underwent oophorectomy by routine laparotomy. Extirpated ovaries underwent MWA at 45 W for 60 (n = 11) or 90 (12) seconds; 3 ovaries did not undergo MWA and served as histologic controls. Ovaries were histologically evaluated for cell viability. Ovaries without viable cells were categorized as completely ablated. Histologic results were used to identify the optimal MWA protocol for use in the subsequent trial. In the second trial, the ovaries of 9 dogs underwent MWA at 45 W for 90 seconds in situ. Ultrasonographic guidance for MWA was deemed unfeasible after evaluation of 1 ovary. The remaining 17 ovaries underwent MWA with laparoscopic guidance, after which routine laparoscopic oophorectomy was performed. Completeness of ablation was histologically assessed for all ovaries. RESULTS: 2 ovaries were excluded from the trial 1 analysis because of equivocal cell viability. Six of 11 ovaries and 10 of 10 ovaries that underwent MWA for 60 and 90 seconds, respectively, were completely ablated. In trial 2, laparoscopic-guided MWA resulted in complete ablation for 12 of 17 ovaries. Dissection of the ovarian bursa for MWA probe placement facilitated complete ablation. CONCLUSIONS AND CLINICAL RELEVANCE: Laparoscopic-guided MWA at 45 W for 90 seconds was feasible, safe, and effective for complete ablation of clinically normal ovaries in dogs.
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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 | 0.001 | 0.003 |
| 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".