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Record W3112667673 · doi:10.24875/ciru.20000879

Complicaciones trombóticas en COVID-19 grave: enfoque en tromboembolia venosa, tromboprofilaxis y anticoagulación

2020· article· es· W3112667673 on OpenAlexaff
Mateo Porres‐Aguilar, María Cristina Guerrero-de León, Flavio Adrián Grimaldo-Gómez, Raúl Izaguirre-Ávila, Alfredo Cabrera-Rayo, Luis E. Santos-Martínez, Jorge R. Sánchez-Medina, Mateo Porres‐Muñoz, Raúl Carrillo-Esper

Bibliographic record

VenueCirugía y Cirujanos · 2020
Typearticle
Languagees
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineVirologyDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

La enfermedad grave por coronavirus 2019 (COVID-19) está causada por el Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) y predispone a complicaciones trombóticas. En esta revisión se aborda de manera práctica la estrecha relación entre la tromboembolia venosa y la COVID-19, enfatizando aspectos epidemiológicos, factores de riesgo y tromboprofilaxis, así como potenciales opciones de anticoagulación. Actualmente la evidencia científica es muy escasa, pero día a día seguimos aprendiendo, estando atentos a cambios novedosos y dinámicos en esta enfermedad infecciosa e inmunotrombótica emergente.

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 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)0.002
metaresearch head score (Gemma)0.129
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.575
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.129
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.007

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 head0.071
GPT teacher head0.424
Teacher spread0.353 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2020
Admission routes1
Has abstractyes

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