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Table_1_The role of vitamin C in the prevention of pancreatic cancer: a systematic-review.DOCX

2024· dataset· en· W6946080746 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typedataset
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
Fundersnot available
KeywordsProspective cohort studyCohortCohort studyIncidence (geometry)Mendelian randomizationRandomized controlled trialVitamin

Abstract

fetched live from OpenAlex

Introduction and aim The aim of this systematic review was to assess the role of vitamin C in the prevention of pancreatic cancer (PC). Methods A comprehensive literature search was performed in PubMed, Embase and Web of Science up to August 2023, to identify randomized controlled trials (RCT), cohort studies and mendelian randomization studies based on prospective databases assessing the role of vitamin C in PC prevention. Results A total of twelve studies including European and North-American participants were included: two RCT, three mendelian randomization (MR) studies and seven cohort studies. Both RCT showed high quality in Cochrane risk of bias tool. Only one cohort study had <7 points in Newcastle Ottawa Scale. Both RCT found no association between the intake of 500 mg/day of vitamin C and the incidence of PC. Only one prospective cohort study found an association between vitamin C serum levels and a lower incidence of PC. The remaining cohort studies and MR studies found no association between dietary/supplements intake of vitamin C or circulating vitamin C levels and the incidence of PC. Conclusion There is no supporting evidence that vitamin C prevents PC development. Future prospective quality studies including high-risk populations are needed.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0060.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.065
GPT teacher head0.367
Teacher spread0.302 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2024
Admission routes1
Has abstractyes

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