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2021· article· en· W4210349032 on OpenAlexaboutno aff

Bibliographic record

VenueASAIO Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicHuman auditory perception and evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceBusiness

Abstract

fetched live from OpenAlex

Anne-Marie Guerguerian MD PhD is a Pediatric Intensive Care Physician in the Department of Critical Care Medicine of the Hospital for Sick Children in Toronto, Canada, where she serves as the Medical Director of the Extracorporeal Life Support Program. As a Senior Scientist of the Research Institute, her program of research is focused on developing methods to quantify brain injury during critical illness. At the University of Toronto, she is appointed to the Department of Paediatrics, the Interdepartmental Division of Critical Care Medicine, and to the Institutes of Medical Sciences, Biomedical Engineering, and Health Policy and Management. As a Clinician Scientist, she volunteers for the Extracorporeal Life Support Organization, and pediatric research resuscitation task forces of the Heart and Stroke Foundation of Canada, the International Liaison Committee on Resuscitation, and for the Get With The Guidelines’ American Heart Association.Dr. Lakshmi Raman, an Associate Professor of Pediatrics, is currently the Medical Director of the Pediatric and Neonatal Extracorporeal Life Support (ECLS) program at Dallas Children’s Medical Center in Dallas Texas, an ELSO center of Excellence. She is currently the Chair of the Publications committee at ELSO which oversees the Guidelines and protocols. Dr. Raman’s research interest is, understanding neurological injuries on extracorporeal membrane oxygenation (ECMO). Dr. Raman has authored more than 30 peer-reviewed publications and currently directs an ELSO-endorsed educational course to teach ECLS in Dallas, Texas.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0230.002

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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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