Comparison of lateral surgical margins of up to two centimeters with margins of three centimeters for achieving tumor-free histologic margins following excision of grade I or II cutaneous mast cell tumors in dogs
Bibliographic record
Abstract
OBJECTIVE: To determine whether conservative lateral surgical margins (equal to tumor diameter for tumors < 2 cm in diameter or 2 cm for larger tumors) were noninferior to wide (3-cm) lateral surgical margins for achieving tumor-free histologic margins following excision of grade I and II cutaneous mast cell tumors (MCTs) in dogs. ANIMALS: 83 grade I and II MCTs excised with a deep surgical fascial margin and requisite lateral surgical margins from 68 dogs from 2007 to 2017. Tumors representing scar revision or local recurrence were excluded. PROCEDURES: A pathology department database was searched to identify qualifying MCTs, and medical records were cross-referenced to obtain data regarding patients and tumors. Outcome (complete vs incomplete excision as histologically determined) was compared between conservative- and wide-margin groups. A noninferiority margin of ≥ 0.9 was used for the risk ratio (probability of complete excision for the conservative- vs wide-margin group), implying that noninferiority would be established if the data indicated that the true risk of complete excision with the conservative-margin approach was at worst 90% of that for the wide-margin approach. RESULTS: The proportion of excised MCTs with tumor-free histologic margins was similar between the conservative- (43/46 [93%]) and wide- (34/37 [92%]) margin groups. There were no differences in tumor diameter or location between treatment groups. The risk ratio (1.02; 95% confidence interval, 0.89 to 1.19) met the criterion for noninferiority. CONCLUSIONS AND CLINICAL RELEVANCE: 2020;256:567-572.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| 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".