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Record W3018872551 · doi:10.1093/jjco/hyaa057

Age-specific cancer incidence rate in the world

2020· article· en· W3018872551 on OpenAlex
Tomohiro Matsuda, Kumiko Saika

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJapanese Journal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple and Secondary Primary Cancers
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancer incidenceCancerIncidence (geometry)OncologyInternal medicine

Abstract

fetched live from OpenAlex

In order to compare the age-specific cancer incidence rate between Japan and other countries, we abstracted cancer incidence rate from the Cancer Incidence in Five Continents Vol. XI (CI5) (1). The International Agency for Research on Cancer provides the CI5 databases on the incidence of cancer recorded by cancer registries (regional and national) worldwide. We used cancer incidence rate in five countries in Asia (China, India, Japan, the Republic of Korea and Thailand), three countries in America (the USA, Canada and Brazil), two countries in Oceania (Australia and New Zealand) and four countries in Europe (the UK, France and Germany and Italy). Some countries have plural cancer registries, and we aggregated all registries to calculate the incidence rate in the countries from the CI5-XI database. The year of cancer diagnosis was from 2008 to 2012. All cancer were coded as C00-97. Figure 1 shows age-specific cancer incidence rate in male by countries, studied. In Asia except for Japan and Korea, the overall incidence rate was lower than the other two areas. In addition, variance of incidence among the studied countries was larger in Asia than those in America and Oceania and Europe. The shape of curve seemed linear in America and Oceania and had “S” shape in Asia. In Europe, a slowdown of cancer incidence increase was observed around the age of 35. Childhood cancer incidence rates were similar in Asia and in America and Oceania; however, the incidence in the age group 5–14 was higher in Europe compared with the other two areas. The incidence in the AYA generation was also higher in Europe. Cancer incidence in the younger age groups (−40) is lower in Asia except Korea; it reached at 100/100 000 around the age of 40; however, in America and Oceania, and Europe, incidence exceeded 100/100 000 in their 30s. Incidence increased then rapidly in Japan until the age of 55. In America and Oceania, increase was constant until the age of 65 and slowed down until the highest age group. The shape of incidence was similar to that in Asia; increase was steep until the age of 65.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.219
GPT teacher head0.476
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it