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Record W2935449958 · doi:10.1016/s0140-6736(18)32592-3

Clinical and biological predictors of response to standardised paediatric colitis therapy (PROTECT): a multicentre inception cohort study

2019· article· en· W2935449958 on OpenAlexaff
Jeffrey S. Hyams, Sonia Thomas, Nathan Gotman, Yael Haberman, Rebekah Karns, Melanie Schirmer, Angela Mo, David R. Mack, Brendan Boyle, Anne M. Griffiths, Neal S. LeLeiko, Cary G. Sauer, David J. Keljo, James Markowitz, Susan S. Baker, Joel R. Rosh, Robert N. Baldassano, Ashish Patel, Marian Pfefferkorn, Anthony Otley, Melvin B. Heyman, Joshua D. Noe, Maria Oliva‐Hemker, Paul A. Rufo, Jennifer Strople, David Ziring, Stephen L. Guthery, Boris Sudel, Keith Benkov, Prateek Wali, Dedrick E. Moulton, Jonathan Evans, Michael D. Kappelman, Miriam Marquis, Francisco Sylvester, Margaret H. Collins, Suresh Venkateswaran, Marla Dubinsky, Vin Tangpricha, Krista Spada, Bradley Saul, Jessie Wang, José Serrano, Kevin A. Hommel, Urko M. Marigorta, Greg Gibson, Ramnik J. Xavier, Subra Kugathasan, Thomas D. Walters, Lee A. Denson

Bibliographic record

VenueThe Lancet · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsIzaak Walton Killam Health CentreHospital for Sick ChildrenUniversity of OttawaChildren's Hospital of Eastern Ontario
FundersNational Center for Complementary and Integrative HealthNational Institute of Diabetes and Digestive and Kidney DiseasesShireBroad InstituteCrohn's and Colitis Foundation
KeywordsMedicineMesalazineInternal medicineUlcerative colitisCohortPopulationCohort studyLogistic regressionColectomyInflammatory bowel diseaseDisease

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.294
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), 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

Citations166
Published2019
Admission routes1
Has abstractno

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