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Record W2036497729 · doi:10.1055/s-2006-946909

Inhibitor Development in Hemophiliacs: The Roles of Genetic versus Environmental Factors

2006· review· en· W2036497729 on OpenAlexaff
Christine Lee, David Lillicrap, Jan Astermark

Bibliographic record

VenueSeminars in Thrombosis and Hemostasis · 2006
Typereview
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsMajor histocompatibility complexDiseaseImmune systemImmunologyAlleleMutationAntibodyMedicineGeneRisk factorHistocompatibilityGeneticsBiologyHuman leukocyte antigenAntigenInternal medicine

Abstract

fetched live from OpenAlex

Approximately 5 to 7% of patients with hemophilia A have inhibitory antibodies to factor (F) VIII, which increases to approximately 13% in patients with severe disease. The strongest determinant of the risk of inhibitor development identified is the type of mutation in the FVIII gene that gives rise to the disease. However, accumulating evidence clearly indicates that other genetic factors (e.g., major histocompatibility complex alleles and other immune-modulatory genes) and factors associated with treatment (e.g., type of FVIII concentrate, route of administration, and age of first exposure) may also influence the risk of inhibitor development. There is much interest in identifying such genetic and treatment-related factors to help minimize the risk of inhibitor development and improve treatment outcomes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.080
GPT teacher head0.356
Teacher spread0.276 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations41
Published2006
Admission routes1
Has abstractyes

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