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Record W4414440902 · doi:10.1016/j.rpth.2025.103188

More real-world evidence on the impact of emicizumab

2025· article· en· W4414440902 on OpenAlexaff
Jerome Teitel

Bibliographic record

VenueResearch and Practice in Thrombosis and Haemostasis · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsSt. Michael's Hospital
FundersF. Hoffmann-La Roche
KeywordsContext (archaeology)Component (thermodynamics)Work (physics)Identification (biology)Production (economics)

Abstract

fetched live from OpenAlex

In this issue of Research and Practice in Thrombosis and Haemostasis, Wall et al. [1] report the results of a 3-year study on UK patients with severe hemophilia A (SHA) without inhibitors who were given the choice of switching to emicizumab for prophylaxis or remaining on factor (F)VIII concentrate [1]. Since access and cost were not barriers to treatment choice, this national cohort study provides insight into the acceptance of emicizumab by patients and their health care teams and data on how their outcomes compared with outcomes of those who chose to remain on conventional FVIII prophylaxis.

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)0.032
metaresearch head score (Gemma)0.118
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.032
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.118
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0020.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0240.002

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 head0.315
GPT teacher head0.541
Teacher spread0.226 · 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 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

Citations0
Published2025
Admission routes1
Has abstractno

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