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Record W2807820203 · doi:10.3748/wjg.v24.i23.2518

Comparing outcomes for endoscopic submucosal dissection between Eastern and Western countries: A systematic review and meta-analysis

2018· review· en· W2807820203 on OpenAlexafffund
Dane Christina Daoud, Nicolas Suter, Madéleine Durand, Mickaël Bouin, B Faulques, Daniel von Renteln

Bibliographic record

VenueWorld Journal of Gastroenterology · 2018
Typereview
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersMcGill University Health Centre
KeywordsEndoscopic submucosal dissectionMeta-analysisMedicineMEDLINEEndoscopic mucosal resectionSurgeryCINAHLCochrane LibraryGeneral surgerySystematic reviewResectionInternal medicinePsychological intervention

Abstract

fetched live from OpenAlex

AIM: To compare endoscopic submucosal dissection (ESD) outcomes between Eastern and Western countries. METHODS: or R0 resection rates. Secondary outcomes were complication rates, local recurrence rates and procedure times. RESULTS: 77 min). CONCLUSION: Eastern countries show better ESD outcomes compared to Western countries. Availability of local ESD expertise and regional outcomes should be considered for decision making to treat gastrointestinal lesions with ESD.

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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.015
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.101
GPT teacher head0.372
Teacher spread0.271 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations84
Published2018
Admission routes2
Has abstractyes

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