MétaCan
Menu
Back to cohort
Record W4395053070 · doi:10.1055/s-0044-1782968

Establishing Standards for Gastrointestinal Endoscopic-Related Fluoroscopy: An International Expert Consensus Using a Modified Delphi Process

2024· article· en· W4395053070 on OpenAlexaff
Kareem Khalaf, Katarzyna M. Pawlak, Douglas G. Adler, Asma Alkandari, Alan Barkun, Todd H. Baron, Robert Bechara, Tyler M. Berzin, Cecilia Binda, Ming‐Yan Cai, Silvia Carrara, Y. I. Chen, Eduardo Guimarães Hourneaux de Moura, Nauzer Forbes, Alessandro Fugazza, Cesare Hassan, Philip James, Michel Kahaleh, Harry Martin, Roberta Maselli, Gary R. May, J. Mosko, Ganiyat K. Oyeleke, B Petersen, Alessandro Repici, Payal Saxena, Amrita Sethi, Reem Z. Sharaiha, Marco Spadaccini, Raymond S. Tang, Christopher Teshima, Mariano Villarroel, Jeanin E. van Hooft, Rogier P. Voermans, Daniel von Renteln, Catharine M. Walsh, Tricia Aberin, Dawn Banavage, Jie Chen, James Clancy, Henrik Drake, Mendeleev Im, Chor Ping Low, Alexandra Myszko, Kaela Navarro, Jeremy A. Redman, W. Reyes, F.S. Weinstein, Yoshinori Fujiyoshi, A Mokhtar, C. Na, Daniel Tham, Nikko Gimpaya, Samir C. Grover, Nicolas Calo

Bibliographic record

VenueEndoscopy · 2024
Typearticle
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsQueen's UniversityCentre Hospitalier de l’Université de MontréalUniversity of CalgaryMcGill UniversitySickKids FoundationToronto General HospitalSt. Michael's Hospital
Fundersnot available
KeywordsMedicineFluoroscopyDelphi methodDelphiProcess (computing)Medical physicsEndoscopyRadiologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Aims The use of fluoroscopy in gastrointestinal endoscopic procedures offers valuable insights but also raises concerns about radiation exposure. This study aims to develop evidence-based guidelines for the safe and effective use of fluoroscopy in such procedures, prioritizing the safety of patients and healthcare workers.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.045
GPT teacher head0.396
Teacher spread0.351 · 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 designBench or experimental
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueEndoscopySame topicEsophageal and GI PathologyFrench-language works237,207