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Record W2919311410 · doi:10.1111/bjh.15813

Fetal and neonatal alloimmune thrombocytopenia: recommendations for evidence‐based practice, an international approach

2019· review· en· W2919311410 on OpenAlexafffund
Lani Lieberman, Andreas Greinacher, Michael Murphy, James B. Bussel, Tamam Bakchoul, Stacy Corke, Mette Kjær, Jens Kjeldsen‐Kragh, Gérald Bertrand, Dick Oepkes, Jillian M. Baker, Heather Hume, Edwin Massey, Cécile Kaplan, Donald M. Arnold, Shoma Baidya, Greg Ryan, Helen Savoia, Denise Landry, Nadine Shehata

Bibliographic record

VenueBritish Journal of Haematology · 2019
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMount Sinai HospitalCanadian Blood ServicesCanadian Red Cross SocietyUniversité de MontréalMcMaster UniversityCentre Hospitalier Universitaire Sainte-JustineUniversity Health NetworkUniversity of TorontoSickKids FoundationHospital for Sick ChildrenSt. Michael's Hospital
FundersCanadian Blood Services
KeywordsNeonatal alloimmune thrombocytopeniaMedicineObstetricsPregnancyFetusPlatelet transfusionGestationPediatricsPlateletImmunologyBiology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.019
metaresearch head score (Gemma)0.044
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 score0.019
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0170.012
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0070.004
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0110.004

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 head0.121
GPT teacher head0.417
Teacher spread0.296 · 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

Citations114
Published2019
Admission routes2
Has abstractyes

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