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Record W1983489842 · doi:10.1177/0272989x03261568

Estimating the Prognosis of Hepatitis C Patients Infected by Transfusion in Canada between 1986 and 1990

2004· article· en· W1983489842 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMedical Decision Making · 2004
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineCirrhosisCohortNatural historyBlood transfusionHepatitis CHepatitis C virusConfidence intervalCohort studyLiver diseaseMarkov modelInternal medicineIntensive care medicinePediatricsMarkov chainVirologyVirusStatistics

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop a natural history model for chronic hepatitis C virus (HCV) infection to determine allocation of compensatory funds to Canadians who acquired HCV through the blood supply from 1986 through 1990. METHODS: A Markov cohort simulation model for HCV prognosis was developed, using content experts, published data, posttransfusion look-back data, and a national survey. RESULTS: The mortality rate in transfusees is high (46% at 10 years), although HCV-related deaths are rare. Only 14% develop cirrhosis at 20 years (95% confidence interval, 0%--44%), but 1 in 4 will eventually develop cirrhosis, and 1 in 8 will die of liver disease. CONCLUSIONS: This unique application of Markov cohort simulation and epidemiologic methods provides a state-of-the-art estimate of HCV prognosis and has allowed compensation decisions to be based on the best available evidence.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.409
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
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 head0.017
GPT teacher head0.313
Teacher spread0.296 · 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