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Record W2970996142 · doi:10.1016/j.recesp.2019.02.017

Impacto del bloqueo del sistema renina-angiotensina en el pronóstico del síndrome coronario agudo en función de la fracción de eyección

2019· article· es· W2970996142 on OpenAlexaff
Sergio Raposeiras‐Roubín, Emad Abu‐Assi, María Cespón‐Fernández, Borja Ibáñez, José Manuel García‐Ruiz, Fabrizio D’Ascenzo, Josè P.S. Henriques, Jorge Saucedo, Berenice Caneiro‐Queija, Rafael Cobas-Paz, Isabel Muñoz‐Pousa, Stephen B. Wilton, José Ramón González‐Juanatey, Wouter J. Kikkert, Iván J. Núñez‐Gil, Albert Ariza‐Solé, Xiantao Song, Dimitrios Alexopoulos, Christoph Liebetrau, Tetsuma Kawaji, Fiorenzo Gaïta, Zenon Huczek, Shaoping Nie, Yan Yan, Toshiharu Fujii, Luis Correia, Masa‐aki Kawashiri, Saško Kedev, Danielle A. Southern, Emilio Alfonso, Belén Terol, Alberto Garay, Dongfeng Zhang, Yalei Chen, Ioanna Xanthopoulou, Neriman Osman, Helge Möllmann, Hiroki Shiomi, Francesca Giordana, Michał Kowara, Krzysztof J. Filipiak‬, Xiao Wang, Jingyao Fan, Yuji Ikari, Takuya Nakahayshi, Kenji Sakata, Masakazu Yamagishi, Oliver Kalpak, Andrés Íñiguez

Bibliographic record

VenueRevista Española de Cardiología · 2019
Typearticle
Languagees
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsLibin Cardiovascular Institute of Alberta
Fundersnot available
KeywordsMedicineGynecology

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)0.004
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.323
Teacher spread0.312 · 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

Citations10
Published2019
Admission routes1
Has abstractno

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