Bibliographic record
Abstract
#### Summary points Most melanomas that are detected and treated early are cured. However, advanced disease carries a dismal diagnosis, and timely intervention from members of the multidisciplinary skin cancer team at all stages of the disease is essential to maximise cure rates. The management of patients with incurable disease is highly specialised and requires the input of surgeons, medical and clinical oncologists, palliative care teams, and clinical nurse specialists. In the second of this two part series on melanoma we review its management from primary lesion through to metastatic disease. #### Sources and selection criteria We used Medline (1966-2008), Cochrane Library, and Embase (1980-2008) to identify studies and meta-analyses for this review. The search string included the terms melanoma, adjuvant and metastatic therapy, wide local excision, and sentinel lymph node biopsy. We accessed the websites of the National Institute for Health and Clinical Excellence, National Cancer Research Network, and National Cancer Research Institute for guidelines and current trials in the United Kingdom. In the past, suspicious lesions were often removed in primary care. However, recent national guidance recommends that patients with suspicious pigmented lesions are referred to a specialist member of the hospital based skin cancer team using the two week cancer wait procedure.1 2 This has been the subject of much debate and if fully implemented will result in a change in practice for many general practitioners. Primary melanoma is often difficult to diagnose, even for those with a specialist training. A prospective study showed …
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".