Classification of positive margins after resection of soft-tissue sarcoma of the limb predicts the risk of local recurrence
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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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".