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Record W2153502375 · doi:10.1161/atvbaha.107.148304

Inhibitors of Factor VIIa/Tissue Factor

2007· review· en· W2153502375 on OpenAlexaff
Rebecca A. Shirk, George P. Vlasuk

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2007
Typereview
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsTissue factorSerine proteaseCoagulationFactor VIIaZymogenThrombusProteaseProtein CMedicinePharmacologyChemistryBiochemistryEnzymeInternal medicine

Abstract

fetched live from OpenAlex

The formation of the proteolytic complex composed of the serine protease Factor VIIa and the cell-associated glycoprotein tissue factor (FVIIa/TF) initiates a cascade of amplified zymogen activation reactions leading to thrombus formation. The critical role of the coagulation cascade in pathological thrombosis has been the basis for significant efforts to design selective inhibitors of the protease components as new anticoagulant alternatives for the treatment of thrombotic diseases. However, for the new generation of anticoagulant drugs in development that primarily target protease complexes distal from FVIIa/TF, the differential between efficacy and safety as defined by bleeding is unresolved. Targeting the FVIIa/TF complex has several theoretical advantages that exploit the amplified nature of the coagulation cascade. However, progress on the development of clinical-stage FVIIa/TF-based anticoagulants has not been as successful to date. This review summarizes recent efforts in the discovery of synthetic inhibitors of FVIIa/TF.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.004

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 head0.140
GPT teacher head0.386
Teacher spread0.247 · 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
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

Citations39
Published2007
Admission routes1
Has abstractyes

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