TECHNICAL ASPECTS OF LIMB AND JOINT SALVAGE SURGERY FOR THE MANAGEMENT OF AGGRESSIVE JUXTA-ARTICULAR AND PERIACETABULAR BONE TUMORS
Bibliographic record
Abstract
To elaborate upon the complex variety of successful reconstructive techniques for limb salvage surgery for the management of aggressive juxta-articular and peri-acetabular bone tumors. Limb sparing surgery, while complex, continues to gain wider acceptance among an increasing number of highly specialised musculoskeletal oncology surgeons. The collective experience of the Musculoskeletal Sarcoma Group at The University of Calgary has utilised a variety of limb and joint salvage techniques in its armamentarium for reconstruction of such cases. Whether malignant or benign, aggressive lesions occur at or near the joint resulting in marked subchondral bone destruction or pathologic fractures. comprehensive stepwise plan can result in a stable, pain free and functional joint with limb sparing. The author has utilised local tumor removal and cementation with polymethylmethacrylate with and without secondary internal fixation. ome cases have been amenable to massive osteoarticular allografts, and more recently, tumor endoprostheses. The North American experience with massive oncology prostheses is growing, resulting in increased opportunities for limb and joint salvage surgery with decreased morbidity and complications. his presentation will review the experience of the principal author’s work in limb and joint-sparing bone tumor surgery over the past 18 years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".