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Record W2127149281 · doi:10.1002/pbc.24341

Positioning new treatments in the management of immune thrombocytopenia

2012· review· en· W2127149281 on OpenAlexafffund
Donald M. Arnold

Bibliographic record

VenuePediatric Blood & Cancer · 2012
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster UniversityCanadian Blood Services
FundersCanadian Institutes of Health ResearchAmgen
KeywordsMedicineRituximabImmune thrombocytopeniaThrombopoietinSplenectomyPlateletDosingThrombopoietin receptorRomiplostimImmune systemImmunologyIntensive care medicineInternal medicineAntibodySpleen

Abstract

fetched live from OpenAlex

Immune thrombocytopenia (ITP) is a syndrome characterized by low platelet counts and an increased risk of bleeding. For most children, ITP is a self-limiting disease; however, for some children and most adults, thrombocytopenia can become chronic. Newer therapies for ITP include rituximab and thrombopoietin (TPO) receptor agonists. Rituximab is a useful second-line therapy and may be splenectomy-sparing. Thrombopoeitin receptor agonists have demonstrated large treatment effects with respect to increasing platelet levels; however, they require maintenance dosing. This review summarizes how these new agents might be positioned in the management of patients with chronic ITP.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.052
GPT teacher head0.353
Teacher spread0.301 · 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

Citations25
Published2012
Admission routes2
Has abstractyes

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