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Record W2039680587 · doi:10.1080/01635581.2013.779384

Cooking Methods and Esophageal Squamous Cell Carcinoma in High-Risk Areas of Iran

2013· article· en· W2039680587 on OpenAlexaff
Roya Hakami, Arash Etemadi, Farin Kamangar, Akram Pourshams, Javad Mohtadinia, Mehdi Saberi Firoozi, Nicholas Birkett, Paolo Boffetta, Sanford M. Dawsey, Reza Malekzadeh

Bibliographic record

VenueNutrition and Cancer · 2013
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsUniversity of Ottawa
FundersNational Institutes of HealthTabriz University of Medical Sciences
KeywordsMedicineCooking methodsCooking oilEtiologyEsophageal squamous cell carcinomaEnvironmental healthEsophageal cancerInternal medicineFood scienceGastroenterologyCarcinomaCancer

Abstract

fetched live from OpenAlex

Cooking methods have been implicated in the etiology of gastrointestinal cancers, reflecting exposure to potential carcinogens as results of cooking. We used a validated food frequency questionnaire and a pretested cooking method questionnaire in 3 groups: 40 esophageal squamous cell carcinoma (ESCC) cases from a high-risk area in northeast of Iran, 40 healthy subjects from the same high-risk area, and 40 healthy subjects from a low-risk area in Southern Iran. We compared the frequency of boiling, grilling, and frying, and the frying score among these 3 groups. We also calculated "frying index" by multiplying the frequency of each fried food item by its frying score. Mean frying to boiling ratios were 18.2:1, 12.8:1, and 2.6:1 for cases, high-risk controls, and low-risk controls, respectively (P < 0.01). Reuse of cooking oil for frying was reported in 37.5% of the ESCC cases, 25% of high-risk controls, and 7.5% of low-risk controls (P < 0.001). Frying index was higher in the high-risk than in the low-risk controls (P < 0.001) and in cases than in the high-risk controls (P < 0.05) after adjusting for smoking, opium use, rural residence, education, and ethnicity. High-temperature cooking and frying may be associated with increased risk of ESCC in high-risk areas.

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 score0.120
Threshold uncertainty score1.000

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 head0.024
GPT teacher head0.340
Teacher spread0.316 · 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

Citations26
Published2013
Admission routes1
Has abstractyes

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