Spine Oncology – Primary Spine Tumors
Bibliographic record
Abstract
Primary tumors originating from the spine are very complex and challenging entities to treat. Due to their rarity, a multicenter collaborative network is essential to shepherd the best research and contribute to the dissemination of the best evidence possible. Over the last few years, several advances have occurred in many different fields. Surgery is still the cornerstone of treatment in most cases. The occasional suboptimal outcomes and high morbidity of surgical treatment have however encouraged professionals caring for these patients to explore safer treatment options and alternatives or adjuncts to surgical treatment. A number of novel treatment strategies have emerged from the medical, interventional radiology, radiation oncology, and molecular worlds. This has truly positioned primary spine tumors at the forefront of multidisciplinary care. This article discusses these recent advances in detail to equip the oncologic spine surgeon and their team to better counsel and treat these patients. Most of these advances allow for a more tailored, efficient, and, most importantly, less morbid management of primary spine tumors. Some of these advances are still under investigation, however, and evidence-based oncological principles should still be strongly encouraged.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".