International variations in carcinoma and melanoma incidence in children and adolescents
Bibliographic record
Abstract
In order to compare the subtype distribution of carcinoma and melanoma in children and adolescents between Japan and other countries, we extracted information on cancer incidence in children and adolescents from the third volume of the International Incidence of Childhood Cancer series (IICC-3) (1). The IICC-3 reports the number or incidence rates of cancers diagnosed in childhood and adolescence, from cancer registries (regional or national) worldwide. We analysed carcinoma and melanoma incidence in four countries in Asia (Japan, China, the Republic of Korea and Thailand), two countries in Africa (Egypt and Uganda), four countries in the Americas (North: The United States of America and Canada, Latin and Caribbean: Brazil and Colombia), three countries in Europe (the United Kingdom [UK], France and Germany) and two countries in Oceania (Australia and New Zealand). Information from the Republic of Korea, USA, UK, Australia and New Zealand was obtained at the national level, and that from the other countries was extracted from one or multiple regional cancer registries. The years of incidence included in the analyses varied from country to country, ranging from 1990 to 2014, with the shortest being 12 years (Egypt: 1999–2010, UK: 2000–2011) and the longest being 24 years (Japan and China: both 1990–2013). In this study, we compared the incidence and proportional distribution of carcinoma and melanoma subtypes in children (0–14 years old) and adolescents (15–19 years old) between these countries.
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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 | 0.000 |
| 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".