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Record W2587952628 · doi:10.1097/mpg.0000000000001547

Temporal Trend of Pediatric Inflammatory Bowel Disease

2017· article· en· W2587952628 on OpenAlexaff
Takashi Ishige, Takeshi Tomomasa, Reiko Hatori, Maiko Tatsuki, Yoshiko Igarashi, Kazuhiko Sekine, Hirokazu Arakawa

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseIncidence (geometry)Young adultUlcerative colitisPediatricsDiseaseEpidemiologyDemographyInternal medicine

Abstract

fetched live from OpenAlex

Increased incidence and prevalence of pediatric inflammatory bowel disease (IBD) have been reported in Western countries. Changes in the prevalence of pediatric IBD in Asian countries, however, remain unclear. We evaluated the changes in the prevalence of IBD among Japanese adults and children from 2004 to 2013, by using the Japanese national registry data of patients receiving financial aid. Data from children (ages 0-19 years) were compared with those from young adults (ages 20-39 years). In 2004, age-standardized prevalences of Crohn disease (CD) and ulcerative colitis (UC) among children were 4.2 of 100,000 and 11.0 of 100,000, respectively. The corresponding prevalences among young adults were 41.0 of 100,000 and 89.8 of 100,000, respectively. In 2013, age-standardized prevalences of pediatric CD and UC were 7.2 of 100,000 and 15.0 of 100,000, respectively. During this period, prevalence of pediatric CD increased by 73.8% among children and by 49.0% in young adults. The prevalence of UC increased by 45.0% among children, and by 73.7% among young adults.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.235
Teacher spread0.228 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations57
Published2017
Admission routes1
Has abstractyes

Explore more

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