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Record W3042593131 · doi:10.1016/j.jvs.2020.06.112

Managing central venous access during a health care crisis

2020· article· en· W3042593131 on OpenAlexaff
Tristen T. Chun, Dejah R. Judelson, David A. Rigberg, Peter F. Lawrence, Robert Cuff, Sherene Shalhub, Max V. Wohlauer, Christopher J. Abularrage, Papapetrou Anastasios, Shipra Arya, Bernadette Aulivola, Melissa Baldwin, Donald T. Baril, Carlos F. Bechara, William E. Beckerman, Christian‐Alexander Behrendt, Filippo Benedetto, Lisa Bennett, Kristofer M. Charlton-Ouw, Amit Chawla, Matthew C. Chia, Sungsin Cho, Andrew M.T.L. Choong, Elizabeth L. Chou, Anastasiadou Christiana, Raphaël Coscas, Giovanni De Caridi, Sharif H. Ellozy, Yana Etkin, Peter L. Faries, Adrian T. Fung, Andrew A. Gonzalez, Claire L. Griffin, London Guidry, Nalaka Gunawansa, Gary A. Gwertzman, Daniel K. Han, Caitlin W. Hicks, Carlos A. Hinojosa, York Hsiang, Nicole Ilonzo, Lalithapriya Jayakumar, Jin Hyun Joh, Adam P. Johnson, Loay Kabbani, Melissa R. Keller, Manar Khashram, Issam Koleilat, Bernard Krueger, Akshay Kumar, Cheong Lee, Alice Lee, Mark Levy, C Lewis, Benjamin Lind, Gabriel López-Peña, Jahan Mohebali, Robert G. Molnar, Nicholas J. Morrissey, Raghu L. Motaganahalli, Nicolas J. Mouawad, Daniel H. Newton, Jun Jie Ng, Leigh Ann O’Banion, John Phair, Zoran Rančić, Ajit Rao, Hunter M. Ray, Aksim Rivera, Limael E. Rodríguez, Clifford M. Sales, Garrett A. Salzman, Mark R. Sarfati, Ajay Savlania, Andres Schanzer, Mel J. Sharafuddin, Malachi Sheahan, Sammy Siada, Jeffrey J. Siracuse, Brigitte K. Smith, Ina Soh, Rebecca Sorber, Varuna Sundaram, Scott Sundick, Tadaki M. Tomita, Bradley Trinidad, Shirling Tsai, Ageliki G. Vouyouka, Gregory G. Westin, Michael Williams, Sherry M. Wren, Jane Yang, Jeniann A. Yi, Wei Zhou, Saqib Zia, Karen Woo

Bibliographic record

VenueJournal of Vascular Surgery · 2020
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsUniversity of British Columbia
FundersNational Center for Advancing Translational SciencesUniversity of Texas Health Science Center at San AntonioWeill Cornell Medical CollegeNational Institutes of HealthU.S. Department of Veterans AffairsNorthwell HealthIndiana University HealthUniversity of WashingtonNorthShore University HealthSystemNational Institute of Diabetes and Digestive and Kidney DiseasesJohns Hopkins UniversityVirginia Commonwealth UniversityNorthwestern UniversityMassachusetts General Hospital
KeywordsMedicineVenous accessVascular accessPandemicCoronavirus disease 2019 (COVID-19)Critically illMedical emergencyIntensive care medicine2019-20 coronavirus outbreakHealth careEmergency medicineSurgeryInternal medicineVirologyEconomic growthInfectious disease (medical specialty)Disease

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)0.002
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.052
GPT teacher head0.350
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 designNot applicable
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

Citations24
Published2020
Admission routes1
Has abstractno

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