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Record W3021228277 · doi:10.14740/jocmr4154

The Issue of the Antiphospholipid Antibody Syndrome

2020· review· en· W3021228277 on OpenAlexvenueno aff
Dinaldo Cavalcanti de Oliveira, Augusto Ferreira Correia, Carolina Gomes Cavalcanti de Oliveira

Bibliographic record

VenueJournal of Clinical Medicine Research · 2020
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAntiphospholipid syndromeLivedo reticularisPlasmapheresisAsymptomaticImmunologyAntibodyCatastrophic antiphospholipid syndromeDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Antiphospholipid antibody syndrome (APS) is a state of hypercoagulability secondary to an autoimmune disorder. It is associated with thrombotic events in venous and arterial vessels, obstetric complications characterized by recurrent fetal losses, and increased perinatal morbidity. APS is classified as primary, when not associated with other pathologies; or secondary, when associated with an underlying autoimmune disease with, solid tumor, or hematological disorder. Clinical findings include livedo reticularis, thrombocytopenia or hemolytic anemia, maternal morbidity, and recurrent thrombotic episodes and others. Laboratory tests show circulating antiphospholipid antibodies (aPLs); however, even in the presence of these antibodies, patients can be asymptomatic. Estimates predict that about 5% of the populations have circulating aPLs, but the incidence of APS is only five cases per 100,000 people, as diagnosis of this syndrome requires clinical and laboratory findings to be simultaneously present. In cases of secondary APS, or in acute cases with imminent risk of death (as in catastrophic APS), it may be necessary to reduce aPL serum levels using immunomodulators, immunosuppressants, or plasmapheresis, in order to treat the associated pathologies. In other situations, the use of immunotherapy is not indicated. In other patients heparin, aspirin or anticoagulants either alone or associated should be administered depending on each specific case.

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)0.003
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.004

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 head0.350
GPT teacher head0.620
Teacher spread0.271 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

Explore more

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