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Record W3128850184 · doi:10.1007/s12630-021-01918-2

Femoral and popliteal venous Doppler during prone and supine position in COVID-19 patients: a potential diagnostic tool to detect abnormal right ventricular function

2021· letter· en· W3128850184 on OpenAlexafffund
Alexandra Malinovska, Ketina Arslani, Núria Zellweger, Cathérine Gebhard, William Beaubien‐Souligny, Alexander Calderone, Martin Siegemund, Markus Aschwanden, André Denault, Caroline E. Gebhard

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2021
Typeletter
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsMontreal Heart InstituteUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersInstitut de Cardiologie de MontréalFondation Institut de Cardiologie de MontréalUniversitätsspital ZürichNational Science FoundationGottfried und Julia Bangerter-Rhyner-StiftungSiemens HealthineersUniversität BaselSanofi GenzymeSchweizerische Akademie der Medizinischen WissenschaftenSanofiSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNovartis FoundationUniversität ZürichRichard I. Kaufman Endowment Fund in Anesthesia and Critical Care
KeywordsSupine positionMedicineCoronavirus disease 2019 (COVID-19)Ventricular functionDoppler effectCardiologyRadiologyInternal medicinePosition (finance)PhysicsDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.192
Teacher spread0.186 · 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 designObservational
Domainnot available
GenreEditorial

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

Citations5
Published2021
Admission routes2
Has abstractno

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