Classification of positive margins after resection of soft-tissue sarcoma of the limb predicts the risk of local recurrence
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
We considered whether a positive margin occurring after resection of a soft-tissue sarcoma of a limb would affect the incidence of local recurrence. Patients with low-grade liposarcomas were expected to be a low-risk group as were those who had positive margins planned before surgery to preserve critical structures. Two groups, however, were expected to be at a higher risk, namely, patients who had undergone unplanned excision elsewhere with a positive margin on re-excision and those with unplanned positive margins occurring during primary resection. Of 566 patients in a prospective database, 87 with positive margins after limb-sparing surgery and adjuvant radiotherapy were grouped according to the clinical scenario by an observer blinded to the outcome. The rate of local recurrence differed significantly between the two low- (4.2% and 3.6%) and the two high-risk groups (31.6% and 37.5%). This classification therefore provides useful information about the incidence of local recurrence after positive-margin resection.
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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 | 0.001 | 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 it