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Record W2755539918 · doi:10.4253/wjge.v9.i9.438

Endoscopic diagnosis and treatment of early esophageal squamous neoplasia

2017· review· en· W2755539918 on OpenAlex
Yuto Shimamura, Takashi Ikeya, Norman E. Marcon, Jeffrey D. Mosko

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWorld Journal of Gastrointestinal Endoscopy · 2017
Typereview
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsChromoendoscopyMedicineEndoscopic mucosal resectionEsophageal cancerEndoscopic treatmentEndoscopyDiseaseEndoscopic submucosal dissectionStage (stratigraphy)LesionRadiofrequency ablationRadiologyCancerInternal medicineSurgeryColorectal cancerAblationColonoscopy

Abstract

fetched live from OpenAlex

Esophageal cancer is one of the leading causes of cancer-related death and is associated with high morbidity and mortality. It carries a poor prognosis as more than half of patients present with advanced and unresectable disease. One contributing factor is the increased risk of lymph node metastases at early stages of disease. As such, it is essential to detect squamous cell neoplasia (SCN) at an early stage. In order to risk stratify lesions, endoscopists must be able to perform image enhanced endoscopy including magnification and Lugol's chromoendoscopy. The assessment of both the horizontal extent and depth of any lesion is also of utmost importance prior to treatment. Endoscopic mucosal resection and submucosal dissection remain the standard of care with literature supportive their respective use. Radiofrequency ablation and other endoscopic treatments are currently available although should not be considered first line at this time. Our objective is to review the current options for the endoscopic diagnosis and treatment of esophageal SCN.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.391
Teacher spread0.308 · 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