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Record W3164081563 · doi:10.1053/j.gastro.2021.04.081

A Summary of the Meetings of the Development of a Core Outcome Set for Therapeutic Studies in Eosinophilic Esophagitis (COREOS) International Multidisciplinary Consensus

2021· letter· en· W3164081563 on OpenAlexaff
Christopher Ma, Alain Schoepfer, Ekaterina Safroneeva, Evan S. Dellon, Albert J. Bredenoord, Mirna Chehade, Margaret H. Collins, Brian G. Feagan, Glenn T. Furuta, Sandeep K. Gupta, Ikuo Hirano, Vipul Jairath, David A. Katzka, Rish K. Pai, Marc E. Rothenberg, Alex Straumann, Seema S. Aceves, Jeffrey A. Alexander, Nicoleta C. Arva, Dan Atkins, Luc Biedermann, Carine Blanchard, Antonella Cianferoni, Constanza Ciriza de los Ríos, Frederic Clayton, Carla M. Davis, Nicola de Bortoli, Jorge Amil Dias, Gary W. Falk, Robert M. Genta, Gisoo Ghaffari, Nirmala Gonsalves, Thomas Greuter, Russell J. Hopp, Karen S. Hsu Blatman, Elizabeth T. Jensen, Doug Johnston, Amir F. Kagalwalla, Helén Larsson, John Leung, Hubert Louis, Joanne C. Masterson, Calies Menard‐Katcher, Paul Menard‐Katcher, Fouad J. Moawad, Amanda B. Muir, Vincent A. Mukkada, Roberto Penagini, Robert D. Pesek, Kathryn A. Peterson, Philip E. Putnam, Alberto Ravelli, Edoardo Savarino, Christoph Schlag, Philipp Schreiner, Dagmar Simon, Thomas C. Smyrk, Jonathan M. Spergel, Tiffany Taft, Ingrid Terreehorst, Tim Vanuytsel, Carina Venter, Mário C. Vieira, Michael Vieth, Berber Vlieg‐Boerstra, Ulrike von Arnim, Marjorie M. Walker, Joshua B. Wechsler, Philip Woodland, John T. Woosley, Guang‐Yu Yang, Noam Zevit

Bibliographic record

VenueGastroenterology · 2021
Typeletter
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsUniversity of Calgary
FundersNational Peanut BoardNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungMedtronicSanofiNovartisNestlé Nutrition InstituteGlaxoSmithKlineNational Institute of Allergy and Infectious DiseasesCelgeneBayerShireAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsEosinophilic esophagitisMultidisciplinary approachMedicineSet (abstract data type)Outcome (game theory)Intensive care medicineInternal medicineComputer scienceDiseaseSociologyMathematicsSocial science

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)0.043
metaresearch head score (Gemma)0.093
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.093
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0050.002
Scholarly communication0.0050.003
Open science0.0040.005
Research integrity0.0350.046
Insufficient payload (model declined to judge)0.0040.004

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 head0.153
GPT teacher head0.375
Teacher spread0.222 · 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.

Study designQualitative
DomainMethods
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

Citations2
Published2021
Admission routes1
Has abstractno

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