[Application of remote sensing navigation system in total knee arthroplasty].
Bibliographic record
Abstract
OBJECTIVE: To explore clinical accuracy of remote sensing navigation alignment (RSNA) system in total knee arthroplasty (TKA) and its influence on postoperative clinical efficacy. METHODS: ;the courses of disease ranged from 3 to 60 months with an average of (21.30±16.44) months;14 patients with grade Ⅲ and 16 patients with grade Ⅳ according to K-L grading. Western Ontario and McMaster Universities (WOMAC) osteoarthritis index and Knee Society score(KSS) were used to evaluate functional recovery of patients. Hip-knee-ankle angle (HKAA), distal femoral valgus angle (FVA) and distal fermoral flexion angle (DFFA) were measured before operation. HKAA and HKAA deviation angle were measured at 1 week after operation, and defective rate of lower limb force line, femur prosthesis valgus angle (FPVA) and femoral prosthesis flexion angle (FPFA), respectively, were calculated. RESULTS: >0.05). CONCLUSION: RSNA system could reduce defective rate of lower limb force line, FPVA deviation angle and FPFA after TKA, which is more accurate and easy to operate than traditional intramedullary localization surgery while ensuring postoperative efficacy.
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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 | 0.001 |
| 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) | 0.002 | 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".