Failure of Radiotracer Migration: Salvaging Sentinel Lymph Node Biopsy in Melanoma Care With Indocyanine Green
Bibliographic record
Abstract
Reducing false negative rates for sentinel lymph node biopsies (SLNB) in melanoma is important to accurately prognosticate and to guide treatment. Traditionally, SLNB has been performed with the adjunct of radiotracers and blue dye. Although sentinel node mapping is highly successful in axillary and inguinal node basins, identification of nodes in the head and neck is not as accurate with traditional methods. One reason for this may be failure of radiotracer migration. To augment standard technique using a radiocolloid, indocyanine green (ICG) combined with near infrared spectroscopy (NIRS), has shown promising results. We demonstrate a case of an individual undergoing SLNB in the head and neck region with failure of radiotracer migration. Identification of a sentinel node was accomplished with the use of ICG and NIRS. This technology offers an opportunity to salvage the SLNB when traditional methods fail.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".