Design of Cervical Pedicle Locator and Three-Dimensional Location of Cervical Pedicle
Bibliographic record
Abstract
STUDY DESIGN: To develop a high-accuracy, easy-manipulated, and low-cost cervical pedicle three-dimensional locator for guiding cervical pedicle screw placement. OBJECTIVES: To improve the safety of cervical pedicle screw insertion, simplify its manipulation, and offer safety guarantees in clinical application. SUMMARY OF BACKGROUND DATA: Because of the complicacy of the anatomic structure of cervical pedicle, clinical application of cervical pedicle screw remained hard to popularize. And recent advances on cervical pedicle location did not simplify the manipulation of procedure significantly. Without aid of locator, distance and angle errors were difficult to control. So far, the only instrument for the location of pedicle "computer-assisted image-guided surgical system" is too expensive for clinical use. Furthermore, it has not yet been documented on location instrument for insertion of cervical pedicle screws. METHODS: The high-accuracy three-dimensional locator, made of stainless steel was designed to aid cervical pedicle nail placement. The cadavers were inserted nails under guidance of the locator that has been input the corresponding parameters collected from CT images. Results were evaluated by CT scans. RESULTS: A total of 90 nails were inserted into cervical pedicles, 90% of which were found right in the pedicles; 10% had pedicle cortex breaches. Parallel offset error of the locator in cross-sectional and lateral CT image that was 0.56 +/- 0.70 and 1.04 +/- 0.99; angular offset error was 1.69 +/- 2.41 and 6.54 +/- 7.08. CONCLUSION: Three-dimensional locator of cervical pedicle and its localization technique achieved good results for individuated screws insertion into cervical pedicles, having such advantages as easy manipulation, high accuracy, and low cost. The system presented safety guarantee to the application and advanced the prevalence of pedicle techniques. Its principium and design were demonstrated feasible.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".