Revision of an unstable HELICA endoprosthesis with a Zurich cementless total hip replacement
Bibliographic record
Abstract
A six-year-old, female, spayed Labrador Retriever was evaluated for progressive lameness of one year duration, ending in non-weight-bearing of the right hindlimb. The dog had a history of severe coxarthrosis of both hip joints, and had a HELICA hip prosthesis implanted in the right hip 18 months before. On survey radiographs, the acetabular and femoral components appeared unstable, with a large void in the proximal femur and a lacy periosteal reaction on the trochanter. Arthrocentesis was performed to rule out septic loosening. As culture samples were negative, the dog underwent surgery. We report the successful revision of an unstable HELICA screw hip prosthesis with a Zurich cementless total hip replacement. The patient had a good clinical and radiological outcome seven months postoperatively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".