Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
STUDY DESIGN: Multicenter, ambispective observational study. OBJECTIVE: To quantify local recurrence and mortality rates after surgical treatment of symptomatic spinal hemangiomas and identify prognostic variables for local disease control. SUMMARY OF BACKGROUND DATA: Spinal hemangiomas are the most common primary tumors of the spine and are generally benign and usually asymptomatic. Because of the rarity of symptomatic spinal hemangiomas, optimal surgical treatment remains unclear. METHODS: AOSpine Knowledge Forum Tumor Investigators created a multicenter database of primary spinal tumors including demographics, presentation, diagnosis, treatment, survival, and recurrence data. Tumors were classified according to Enneking and Weinstein-Boriani-Biagini. Descriptive statistics were summarized and time to mortality and recurrence was determined. RESULTS: Between 1996 and 2012, 68 patients (mean age = 51 yr, SD = 16) underwent surgical treatment of a spinal hemangioma. Epidural disease was present in 55% of patients (n = 33). Pain and neurological compromise were presenting symptoms in 82% (n = 54) and 37% (n = 24) of patients, respectively. Preoperative embolization was performed in 35% of patients (n = 23), 10% (n = 7) had adjuvant radiotherapy, and 81% (n = 55) underwent posterior-alone surgery. The local recurrence rate was 3% (n = 2). Mortality secondary to spinal hemangioma was not observed (mean follow-up = 3.9 yr, SD = 3.8). CONCLUSION: This is the largest multicenter surgical cohort of spinal hemangiomas. Symptomatic spinal hemangiomas are a benign tumor despite frequently presenting with epidural disease and neurological compromise. Thus, formal en bloc resection is not required, and excellent rates of local control and long-term survival can result from aggressive intralesional resection during index surgery. LEVEL OF EVIDENCE: 3.
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.
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) | 0.000 | 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 it