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Challenges of Cholangiocarcinoma Detection in Patients with Primary Sclerosing Cholangitis

2012· article· en· W2017453861 on OpenAlexvenueno aff
James H. Tabibian, Keith D. Lindor

Bibliographic record

VenueJournal of Analytical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsPrimary sclerosing cholangitisMedicineGastroenterologyCirrhosisInternal medicineStage (stratigraphy)Primary biliary cirrhosisDisease

Abstract

fetched live from OpenAlex

Primary sclerosing cholangitis (PSC) is a chronic, cholestatic, idiopathic liver disease characterized by fibro-obliterative inflammation of the hepatic bile ducts. In a clinically significant proportion of patients, PSC progresses to cirrhosis, end-stage liver disease, and in some cases, cholangiocarcinoma (CCA). The development of CCA in PSC is unpredictable, its surveillance and diagnosis complex, and its treatment options limited unless detected early. Herein we provide a focused review of the current literature regarding CCA surveillance in patients with PSC and discuss the diagnostic and management challenges that exist. Where evidence is limited, we present our perspective and approach as well as directions for future research.

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)0.007
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.035
GPT teacher head0.290
Teacher spread0.255 · 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 designObservational
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

Citations27
Published2012
Admission routes1
Has abstractyes

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