Registration Stability of Physical Templates in Hip Surgery
Bibliographic record
Abstract
We tested the registration stability of individualized templates in a consecutive study with 80 patients undergoing hip-resurfacing surgery. These templates physically encode registration and navigation parameters but do not require a computer during the actual surgery. The surgical target was the placement of the femoral guidance pin during hip resurfacing, which is a difficult and highly variable task using conventional instruments. The drill trajectory for the guidance pin of the femoral component was planned on a 3D computer model of the femur derived from a preoperative computed tomography (CT) scan. A surface-matched drilling template was designed to perform mechanical registration on the bone surface and had a hole for the drill guide; the template was created using a rapid prototyping machine. Intraoperatively, the individualized template was positioned on the patient anatomy and the pin was drilled into the femoral neck. The final achieved pin orientation and position were measured using an optoelectronic CT-based navigation system. The measured mean deviation between planned and actual central pin alignment of 0.05° in valgus and 2.8° in anteversion shows that the proposed individualized templates for hip resurfacing have reliable registration.
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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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".