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Record W7132880825

Primary Sclerosing Cholangitis-Individual Patient International Meta-analysis of Biochemical and Clinical Predictors of Outcome

2023· dissertation· W7132880825 on OpenAlexaff
Marwa Ismail

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsInstitute of Health Services and Policy Research
Fundersnot available
KeywordsPrimary sclerosing cholangitisRisk stratificationDiseaseHazard ratioProportional hazards modelRisk assessmentPrimary biliary cirrhosis
DOInot available

Abstract

fetched live from OpenAlex

PSC is an autoimmune disease of the biliary tracts that affects males more than females. Patients with PSC have a variable disease course. The disease hallmark is strictures and dilations involving the bile ducts with an increased risk of cholangiocarcinoma. PSC has a close association with IBD predominantly UC with a higher hazard of developing colon cancer. Risk stratification of PSC patients is crucial for patient education and to guide clinical decisions and transplant efforts. Multiple risk stratification strategies and models have been proposed. In this study, we sought to explore novel risk stratification strategies in addition to longitudinal risk stratification models to identify patients with progressive disease. ALP, TB, Albumin and platelets have a distinctive pattern and levels for patients with progressive disease and can identify them up to 10 years before experiencing death or transplant. Additionally, total bilirubin ULN can be used to discriminate high-risk patients.

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)0.006
metaresearch head score (Gemma)0.010
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: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.020
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.148
GPT teacher head0.421
Teacher spread0.273 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

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