The effect of COVID-19 emergency in the management of melanoma in Italy
Bibliographic record
Abstract
The COVID-19 pandemic has severely hampered the functioning of any health system, absorbing a considerable amount of resources and with the threat of widespread infection in the health services. The present survey has been carried out in Italy to evaluate if and how COVID-19 also affected skin melanoma management. We enrolled 13 Italian centres highly qualified in the diagnosis and care of skin melanoma. We compared a set of information evaluating the amount of activity for melanoma performed during February-April 2020 with the same quarter in 2019. The number of new melanoma diagnosis, biopsies, wide local excisions, overall pathology reports decreased. However, the most severe cases seem promptly managed with sentinel lymph node biopsies, new systemic treatments (north) and the total number of (advanced) treated patients (centre-south). The COVID-19 experience has underlined the need to exploit the help which may come from telemedicine.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".