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Record W2962999280 · doi:10.1177/1756284819863015

Can advanced endoscopic techniques for assessment of mucosal inflammation and healing approximate histology in inflammatory bowel disease?

2019· article· en· W2962999280 on OpenAlex

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

VenueTherapeutic Advances in Gastroenterology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseEndoscopyHistologyGold standard (test)InflammationCryptColorectal cancerPathologyDiseaseRadiologyInternal medicineCancer

Abstract

fetched live from OpenAlex

The targets of therapy in inflammatory bowel disease have transformed in the last few years. The standard definition of mucosal healing assessed using white light standard definition endoscopy is being challenged because even when endoscopy suggests mucosal healing, the presence of histological activity can often still be observed. Of note, microscopic signs of inflammation correlate with clinical outcomes such as risk of relapse, hospitalization and colorectal cancer. Therefore, histological healing has increasingly become an important target to achieve. Advanced endoscopic technologies have been developed and many are starting to be adopted in daily clinical practice. They can provide a more detailed view of the mucosal and vascular architecture almost at the histology level, including crypt, vessel architecture and cellular infiltration. So, these can provide a more accurate definition of mucosal and histological healing. In this review we focus on new advanced endoscopic techniques, and how these have the potential to reduce the gap between histological and mucosal healing.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.278
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