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Updated international consensus report on the investigation and management of primary immune thrombocytopenia

2019· article· en· W4211106014 on OpenAlexaff
Drew Provan, Donald M. Arnold, James B. Bussel, Beng H. Chong, Nichola Cooper, Terry Gernsheimer, Waleed Ghanima, Bertrand Godeau, Tomás José González‐López, John D. Grainger, Ming Hou, Caroline Kruse, Vickie McDonald, Marc Michel, Adrian C. Newland, Sue Pavord, Francesco Rodeghiero, Marie Scully, Yoshiaki Tomiyama, Raymond Wong, Francesco Zaja, David J. Kuter

Bibliographic record

VenueBlood Advances · 2019
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster UniversityCanadian Blood Services
FundersAmgen
KeywordsImmune thrombocytopeniaConsensus conferenceMedicineIntensive care medicineMEDLINEPregnancyExpectant managementImmunologyPolitical scienceInternal medicineAntibody

Abstract

fetched live from OpenAlex

Abstract Over the last decade, there have been numerous developments and changes in treatment practices for the management of patients with immune thrombocytopenia (ITP). This article is an update of the International Consensus Report published in 2010. A critical review was performed to identify all relevant articles published between 2009 and 2018. An expert panel screened, reviewed, and graded the studies and formulated the updated consensus recommendations based on the new data. The final document provides consensus recommendations on the diagnosis and management of ITP in adults, during pregnancy, and in children, as well as quality-of-life considerations.

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)0.061
metaresearch head score (Gemma)0.084
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.061
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.084
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0110.006
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0060.004
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0050.004

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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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

Citations1,090
Published2019
Admission routes1
Has abstractyes

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