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Record W2107471334 · doi:10.1155/2007/910831

Management of Chronic Hepatitis B: Consensus Guidelines

2007· article· en· W2107471334 on OpenAlexafffundvenueabout
Morris Sherman, Stephen D. Shafran, Kelly W. Burak, Karen Doucette, Winnie Wong, Nigel Girgrah, Eric M. Yoshida, Eberhard L. Renner, Philip Wong, Marc Deschênes

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2007
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of ManitobaUniversity of British ColumbiaMcGill UniversityUniversity of CalgaryUniversity of AlbertaUniversity of Toronto
FundersCenters for Disease Control and PreventionDalhousie UniversityUniversity of TorontoUniversité LavalUniversity of AlbertaUniversity of Ottawa
KeywordsChronic hepatitisMedicineHepatitis BFamily medicineHepatitisConsensus conferenceInfectious disease (medical specialty)DiseaseIntensive care medicineImmunologyPathologyInternal medicineVirus

Abstract

fetched live from OpenAlex

The present document presents the proceedings of the consensus development conference on the management of viral hepatitis held in January 2007 under the auspices of the Canadian Association for the Study of the Liver and the Association of Medical Microbiology and Infectious Disease Canada. Several new agents have become available since the last such document was published in 2004, and new information has become available to help assess risk of adverse outcomes and who should be treated. In addition, the participants at the meeting identified a number of structural barriers that exist uniquely in Canada and that prevent physicians from properly managing their patients. The conference discussed the selection of patients for treatment and the drugs that can be used to treat these patients, as well as the treatment of hepatitis B in special populations. The present document should be read in conjunction with the companion document on the management of chronic hepatitis C.

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 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)0.000
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 score0.126
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.040
GPT teacher head0.333
Teacher spread0.293 · 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 teacher head, 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

Citations93
Published2007
Admission routes4
Has abstractyes

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