MétaCan
Menu
Back to cohort
Record W4234111996 · doi:10.3747/co.24.3226

Rising rates of colorectal cancer among younger Iranians: is diet to blame?

2017· article· en· W4234111996 on OpenAlexvenueno aff
Sujana Arani, Mohammad Amin Kerachian

Bibliographic record

VenueCurrent Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColorectal cancerBlamePopulationIncidence (geometry)DemographyYoung adultMortality rateCancerMEDLINEGerontologyEnvironmental healthInternal medicinePsychiatryBiology

Abstract

fetched live from OpenAlex

Background Colorectal cancer (crc) is one of the most prevalent cancers in the world. Although the incidence of crc is currently very low in the older Iranian population compared with Western populations, young Iranians show a rising trend of crc—that is, the age-adjusted rate is close in the young Iranian population compared with the U.S. population, and the rate in older Iranians is much lower.Methods To assess a putative relationship between diet and a rising rate of crc in younger Iranians, a combined text word and mesh heading search strategy identified relevant studies through Google Scholar and medline.Results A critical look at diet among Iranians shows major issues that might be raising the risk for crc. There are also scenarios other than diet for the rise, such as the young age structure of the country. However, the actual scenario is more complex.Conclusions In Iran, crc is one of the most common incident cancers and a common cause of cancer death. Primary and secondary prevention—with attention to a healthy lifestyle, physical activity, and screening—should be enhanced in the general population.

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 score0.217
Threshold uncertainty score0.530

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 head0.113
GPT teacher head0.439
Teacher spread0.327 · 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

Citations29
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCurrent OncologySame topicColorectal Cancer Screening and DetectionFrench-language works237,207