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Record W4402147271 · doi:10.1053/j.gastro.2024.08.021

Development and Validation of an Integrative Risk Score for Future Risk of Crohn’s Disease in Healthy First-Degree Relatives: A Multicenter Prospective Cohort Study

2024· article· en· W4402147271 on OpenAlexafffund
Sun-Ho Lee, Williams Turpin, Osvaldo Espin-Garcia, Wei Xu, Kenneth Croitoru

Bibliographic record

VenueGastroenterology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMemorial University of NewfoundlandCentre Hospitalier Universitaire Sainte-JustineDalhousie UniversityQueen's UniversityMcMaster UniversityUniversity of ManitobaMcGill University Health CentreUniversity of OttawaHôpital Maisonneuve-RosemontPopulation Health Research InstituteChildren's Hospital of Eastern OntarioMount Sinai HospitalPrincess Margaret Cancer CentreUniversity of CalgaryHospital for Sick ChildrenUniversité de MontréalUniversity of AlbertaBC Children's HospitalWestern UniversityUniversity of TorontoSinai Health System
FundersTemerty Faculty of Medicine, University of TorontoCrohn's and Colitis CanadaCanadian Association of GastroenterologyGovernment of OntarioTel Aviv UniversityUniversity of TorontoBC Children's HospitalUniversity of AlbertaCanadian Institutes of Health ResearchLeona M. and Harry B. Helmsley Charitable Trust
KeywordsMedicineProspective cohort studyCrohn's diseaseCohortDiseaseFramingham Risk ScoreCohort studyInternal medicine

Abstract

fetched live from OpenAlex

Despite advances in medical therapy, approximately one-half of patients with Crohn’s disease (CD) develop complications ultimately requiring surgery. Currently, no treatment offers a chance of cure.1,2 The increasing incidence and prevalence of CD globally pose a substantial burden at the population and individual levels. Thus, a better understanding of the early triggers of CD is desperately needed to enhance early detection, improve medical therapy, and offer a possibility of interventions that prevent development of CD.

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 score0.012
Threshold uncertainty score0.640

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 head0.008
GPT teacher head0.260
Teacher spread0.251 · 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

Citations17
Published2024
Admission routes2
Has abstractyes

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