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Record W1985872971 · doi:10.1002/hep.22953

The hepatitis B research network # †

2009· article· en· W1985872971 on OpenAlexaboutno aff
Edward Doo, Jay H. Hoofnagle

Bibliographic record

VenueHepatology · 2009
Typearticle
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsMedicineClinical researchPolitical scienceLiver diseaseAction planHepatitis BViral hepatitisDiseaseFamily medicineImmunologyPathologyManagementInternal medicine

Abstract

fetched live from OpenAlex

I n parallel with the Consensus Development Conference on Management of Chronic Hepatitis B, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH) held the initial organizational steering committee meeting of the Hepatitis B Research Network.The establishment of this network was the centerpiece of a large initiative in hepatitis B that was directed at making progress in the understanding, prevention, and control of this important liver disease.This initiative was the result and a part of the Trans-NIH Action Plan for Liver Disease Research (http://liverplan.niddk.nih.gov) that was published in December 2004 and laid out a series of specific research goals for liver disease research for the next 10 years.The Action Plan represented the collective efforts of more than 250 individuals including liver research investigators, academicians, practicing physicians, researchers and representatives from industry, NIH staff, and lay advocates who worked together to prioritize liver disease research goals.The research goals were directed at specific advances that would translate into substantial improvement in the understanding, prevention, and treatment of liver diseases.Within this report, key research priorities for hepatitis B research were given in the chapter on viral hepatitis, many of which still remain incompletely resolved.To help meet these goals, the NIH sponsored this 2008 Consensus Development Conference on Management of Hepatitis B, but also set into motion a prospective clinical research network of investigators charged with the mission to provide new insights into the pathogenesis of hepatitis B and help define the most appropriate therapy of this disease in its multiple clinical forms and in the different populations that it affects.The creation of a Hepatitis B Research Network was announced in a Request for Applications published in October 11, 2007 using a cooperative agreement (U01) grant mechanism.Grant applications for clinical centers, research cores, and a Data Coordinating Center were received by February 27, 2008, reviewed on July 10-11, 2008, and awarded on September 30, 2008, in time for the initial, organizational meeting of the network to be held at the time of the NIH Consensus Conference.Organizationally, the network is composed of 13 Clinical Centers with expertise in the diagnosis, management, and treatment of chronic hepatitis B; one Data Coordinating Center to provide statistical, protocol, and logistical support for the network; and an Immunology Core to investigate immune factors that are important in hepatitis B. The network will also be supported by a virology testing core and a specimen repository.The NIDDK has committed $45 million over 7 years toward this endeavor.The 13 Clinical Center Principal Investigators (and some sites with multiple Coinvestigators) in alphabetical order are:•

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)0.014
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.097
Threshold uncertainty score0.324

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0970.060

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 head0.074
GPT teacher head0.391
Teacher spread0.317 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2009
Admission routes1
Has abstractyes

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