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Improvements in factor concentrates.

2010· article· en· W20613509 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.

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Algebra and Logic
Canadian institutionsQueen's University
Fundersnot available
KeywordsBrain–computer interfaceAlgebra over a fieldMathematicsComputer scienceArithmeticPure mathematicsPsychologyElectroencephalography

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The aim of this review is to highlight strategies being pursued to enhance current concentrate therapies for the hemophilias. During the past 5 years, significant progress has been made with a variety of protein-engineering initiatives, some of which are already in early-phase clinical trials. RECENT FINDINGS: The standard of care for hemophilia therapy involves the infusion of clotting factor concentrates either at the time of bleeding (on demand therapy) or in a prophylactic schedule to prevent bleeding episodes. This latter approach to therapy has been used in some parts of Europe for several decades and has recently been shown, in a prospective randomized study, to result in a significant reduction in musculoskeletal pathology. The aim of many of the novel concentrates under development is to prolong the half-life of the infused clotting factor and thus to reduce the frequency of infusions. Several different strategies are being evaluated for this purpose including conjugation with hydrophilic polymers and generation of fusion proteins that are recycled by the FcRn receptor. SUMMARY: The speed of progress with the development of several approaches to extend clotting factor half-lives has been encouraging. It is very likely that several of these concentrates will reach the clinic in the near future.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.214
Teacher spread0.199 · 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