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Record W2883421352 · doi:10.1213/xaa.0000000000000841

Real-Time Assessment of Renal Venous Flow by Transesophageal Echography During Cardiac Surgery

2018· article· en· W2883421352 on OpenAlexaff
William Beaubien‐Souligny, André Denault

Bibliographic record

VenueA&A Practice · 2018
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsAnesthesiologyIntensive careMedicineLibrary scienceEndowmentEditorial boardCardiac surgeryPolitical scienceCardiologyAnesthesiaIntensive care medicineLawComputer science

Abstract

fetched live from OpenAlex

Hemodynamic monitoring during cardiac surgery is \ncurrently based on pressure measurements from an \narterial cannula and central venous catheter. While \ncentral venous pressure (CVP) is routinely measured during cardiac surgery, the hemodynamic impact of venous \nhypertension on end-organ perfusion often remains unappreciated. We present a case in which transesophageal \nechography (TEE) was used to observe the impact of CVP \nvariations on intrarenal venous flow velocities during cardiac surgery. The patient provided written permission for \npublication of this report.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.307
Teacher spread0.298 · 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
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

Citations20
Published2018
Admission routes1
Has abstractyes

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