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Record W2294302508 · doi:10.1177/1753495x15601937

Thrombocytopenic syndromes in pregnancy

2015· review· en· W2294302508 on OpenAlex
Matthew Yan, Ann Kinga Malinowski, Nadine Shehata

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueObstetric Medicine · 2015
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMount Sinai HospitalUniversity of Toronto
FundersCanadian Blood Services
KeywordsMedicinePregnancyEtiologyGestationObstetricsPopulationPlateletPediatricsFetusGestational ageInternal medicine

Abstract

fetched live from OpenAlex

The physiological changes in pregnancy result in platelet counts that are lower than in nonpregnant women. Consequently, thrombocytopenia is a common finding occurring in 7-12% of pregnant women. Gestational thrombocytopenia, the most common cause of low platelet counts, tends to be mild in most women and does not affect maternal, fetal or neonatal outcomes. Gestational thrombocytopenia needs to be distinguished from other less common causes of isolated thrombocytopenia, such as immune thrombocytopenia, which affects approximately 3% of thrombocytopenic pregnant women and can lead to neonatal thrombocytopenia. Hypertensive disorders of pregnancy and thrombotic microangiopathies are both associated with thrombocytopenia. They share a considerable number of similar characteristics and are associated with significant maternal and neonatal morbidity and rarely mortality. Accurate identification of the aetiology of thrombocytopenia and appropriate management are integral to optimizing the pregnancy, delivery and neonatal outcomes of this population. Clinical cases are described to illustrate the various aetiologies of thrombocytopenia in pregnancy and their treatment.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.145
GPT teacher head0.393
Teacher spread0.248 · 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