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Record W2978284919 · doi:10.1111/1751-2980.12823

Dietary total antioxidant capacity and risk of ulcerative colitis: A case‐control study

2019· article· en· W2978284919 on OpenAlexaff
Jamal Rahmani, Hamed Kord‐Varkaneh, Paul M. Ryan, Samaneh Rashvand, Cain C. T. Clark, Andrew S. Day, Azita Hekmatdoost

Bibliographic record

VenueJournal of Digestive Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineOdds ratioQuartileUlcerative colitisInternal medicineConfidence intervalCase-control studyVitamin CVitamin EAntioxidantGastroenterologyAntioxidant capacityDiseaseOxidative stressBiochemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: Data on the association between the antioxidant capacity of a diet and the risk of ulcerative colitis (UC) are scarce. This study aimed to assess whether a relationship exists between dietary total antioxidant capacity (TAC) and the odds of UC in Iranian adults. METHODS: In this case-control study, patients with UC and age-matched healthy controls were recruited from a hospital clinic. All participants completed a validated 168-item food frequency questionnaire, the results of which were subsequently used to generate dietary TAC. Ferric reducing-antioxidant power values were used to calculate dietary TAC. RESULTS: (P < 0.01) and calcium (P = 0.02) compared with healthy controls, while the control group had a higher vitamin C intake than the participants with UC (P < 0.01). In a fully adjusted model, participants who were in the highest quartile of dietary TAC had a lower risk of UC (odds ratio 0.11, 95% confidence interval 0.01-0.73). CONCLUSIONS: A higher dietary TAC score was associated with lower odds of UC in this case-control study. Further elucidation of the role of key dietary elements is now warranted.

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 score0.010
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.013
GPT teacher head0.266
Teacher spread0.252 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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