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Record W2139928433 · doi:10.1186/1471-2288-11-135

Study protocol: the empirical investigation of methods to correct for measurement error in biobanks with dietary assessment

2011· article· en· W2139928433 on OpenAlexafffund
Derrick Bennett, Julian Little, L. F. Masson, Cosetta Minelli

Bibliographic record

VenueBMC Medical Research Methodology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsUniversity of Ottawa
FundersUniversity of AberdeenCanadian Institutes of Health ResearchUniversity of Leicester
KeywordsBiobankCompendiumProtocol (science)Nutritional epidemiologyComputer sciencePoolingPopulationData scienceCalibrationHarmonizationManagement scienceData miningEpidemiologyMedicineEnvironmental healthBioinformaticsStatisticsAlternative medicineBiologyGeographyArtificial intelligenceEngineeringMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: The Public Population Project in Genomics (P3G) is an organisation that aims to promote collaboration between researchers in the field of population-based genomics. The main objectives of P3G are to encourage collaboration between researchers and biobankers, optimize study design, promote the harmonization of information use in biobanks, and facilitate transfer of knowledge between interested parties. The importance of calibration and harmonisation of methods for environmental exposure assessment to allow pooling of data across studies in the evaluation of gene-environment interactions has been recognised by P3G, which has set up a methodological group on calibration with the aim of; 1) reviewing the published methodological literature on measurement error correction methods with assumptions and methods of implementation; 2) reviewing the evidence available from published nutritional epidemiological studies that have used a calibration approach; 3) disseminating information in the form of a comparison chart on approaches to perform calibration studies and how to obtain correction factors in order to support research groups collaborating within the P3G network that are unfamiliar with the methods employed; 4) with application to the field of nutritional epidemiology, including gene-diet interactions, ultimately developing a inventory of the typical correction factors for various nutrients. METHODS/DESIGN: Systematic review of (a) the methodological literature on methods to correct for measurement error in epidemiological studies; and (b) studies that have been designed primarily to investigate the association between diet and disease and have also corrected for measurement error in dietary intake. DISCUSSION: The conduct of a systematic review of the methodological literature on calibration will facilitate the evaluation of methods to correct for measurement error and the design of calibration studies for the prospective pooling of biobanks. This could increase the efficiency of the design of such studies, improve statistical power, reduce bias, and aid in the assessment of gene-environment interaction effects in complex diseases. The systematic review of calibration of dietary intake information could inform gene-diet interaction investigations involving the pooling of results from studies with nutritional data collected in different ways.

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)0.034
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.225
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.844
GPT teacher head0.638
Teacher spread0.206 · 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 designObservational
Domainnot available
GenreMethods

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

Citations1
Published2011
Admission routes2
Has abstractyes

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