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Record W3136532060 · doi:10.1093/ecco-jcc/jjab048

Results of the Seventh Scientific Workshop of ECCO: Precision Medicine in IBD—Prediction and Prevention of Inflammatory Bowel Disease

2021· article· en· W3136532060 on OpenAlexaff
Joana Torres, Jonas Halfvarson, Iago Rodríguez–Lago, Charlotte Hedin, Tine Jess, Marla Dubinsky, Kenneth Croitoru, Jean‐Frédéric Colombel

Bibliographic record

VenueJournal of Crohn s and Colitis · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of TorontoMount Sinai Hospital
FundersKU LeuvenCleveland Clinic
KeywordsMedicineInflammatory bowel diseaseCrohn's diseaseInflammatory Bowel DiseasesInternal medicineGastroenterologyDisease

Abstract

fetched live from OpenAlex

Inflammatory bowel disease [IBD] is a complex chronic disorder with no clear aetiology and no known cure. Despite recent advances in overall disease management and improved therapeutics, patients with IBD still experience a substantial burden. Furthermore, as the incidence continues to increase in developing areas of the world, it is expected that the burden of IBD to society will increase and exert tremendous pressure on health care systems worldwide. Therefore, new strategies to prevent the global increase of IBD are urgently required. Data are being progressively acquired on the period preceding disease diagnosis, which support the concept that IBD has a preclinical period that may reveal the triggers of disease and may be amenable to early intervention. Having a better knowledge of this preclinical period will increase the potential not only for improved understanding of disease pathogenesis and improved therapeutics, but also for disease prediction and prevention.

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)0.000
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 score0.507
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.249
Teacher spread0.241 · 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

Citations67
Published2021
Admission routes1
Has abstractyes

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