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Record W3165464773 · doi:10.1016/j.echo.2021.05.012

Normal Values of Cardiac Output and Stroke Volume According to Measurement Technique, Age, Sex, and Ethnicity: Results of the World Alliance of Societies of Echocardiography Study

2021· article· en· W3165464773 on OpenAlexaff
Hena Patel, Tatsuya Miyoshi, Karima Addetia, M.P. Henry, Rodolfo Citro, Masao Daimon, Pedro Gutiérrez Fajardo, Ravi R. Kasliwal, James N. Kirkpatrick, Mark Monaghan, Denisa Muraru, Kofo O. Ogunyankin, Seung Woo Park, Ricardo Ronderos, Anita Sadeghpour, G. Scalia, Masaaki Takeuchi, Wendy Tsang, Edwin S. Tucay, Ana Clara Tude Rodrigues, Vivekanandan Amuthan, Yun Zhang, Marcus Schreckenberg, Michael Blankenhagen, Markus Degel, Alexander Rossmanith, Victor Mor‐Avi, Federico M. Asch, Roberto M. Lang, Aldo Prado, Eduardo Filipini, Agatha Kwon, Samantha Hoschke-Edwards, Tânia Regina Afonso, Babitha Thampinathan, Maala Sooriyakanthan, Tiangang Zhu, Zhilong Wang, Yingbin Wang, Lixue Yin, Shuang Li, R Alagesan, Sowmya Balasubramanian, R.V.A. Ananth, Manish Bansal, Azin Alizadehasl, Luigi P. Badano, Eduardo Bossone, Davide Di Vece, Michele Bellino, Tomoko Nakao, Takayuki Kawata, Megumi Hirokawa, Naoko Sawada, Hye Rim Yun, Ji‐won Hwang

Bibliographic record

VenueJournal of the American Society of Echocardiography · 2021
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
FundersNational Heart, Lung, and Blood InstituteAmerican Society of Echocardiography
KeywordsMedicineStroke volumeCardiologyBody surface areaInternal medicineDoppler echocardiographyCardiac outputStroke (engine)Body mass indexHemodynamicsDemographyBlood pressureHeart rateDiastole

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)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.028
GPT teacher head0.290
Teacher spread0.262 · 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

Citations81
Published2021
Admission routes1
Has abstractno

Explore more

Same venueJournal of the American Society of EchocardiographySame topicHemodynamic Monitoring and TherapyFrench-language works237,207