MétaCan
Menu
Back to cohort
Record W4392624708 · doi:10.1016/j.vgie.2024.03.002

Enhancing closure efficacy in antireflux mucoplasty through endoscopic hand-suturing technique

2024· article· en· W4392624708 on OpenAlexaff
Kei Ushikubo, Haruhiro Inoue, Kazuki Yamamoto, Yuto Shimamura, Mary Raina Angeli Fujiyoshi, Yohei Nishikawa, Akiko Toshimori, Manabu Onimaru

Bibliographic record

VenueVideoGIE · 2024
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineClosure (psychology)SurgeryGeneral surgery

Abstract

fetched live from OpenAlex

We have previously reported the usefulness of antireflux mucosectomy and antireflux mucosal ablation as interventions for addressing proton pump inhibitor refractory/dependent GERD.1-3 Although the effectiveness of antireflux mucosectomy and antireflux mucosal ablation has been confirmed through meta-analyses,4-6 these methods have been reported to result in approximately 5% delayed bleeding, attributed to the necessity for scar contraction following mucous membrane excision and resection. In endoscopic submucosal dissection, it is widely known that closing the defect reduces delayed bleeding.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: Other design
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.328
Teacher spread0.304 · 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 designOther design
Domainnot available
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

Citations5
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueVideoGIESame topicGastroesophageal reflux and treatmentsFrench-language works237,207