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Record W2786978571 · doi:10.1016/j.ijcard.2017.10.103

Development and external validation of a post-discharge bleeding risk score in patients with acute coronary syndrome: The BleeMACS score

2018· article· en· W2786978571 on OpenAlexaff
Sergio Raposeiras‐Roubín, Jonas Faxén, Andrés Íñiguez, Josè P.S. Henriques, Fabrizio D’Ascenzo, Jorge Saucedo, Karolina Szummer, Tomas Jernberg, Stefan James, José Ramón González‐Juanatey, Stephen B. Wilton, Wouter J. Kikkert, Iván J. Núñez‐Gil, Albert Ariza‐Solé, Xiantao Song, Dimitrios Alexopoulos, Christoph Liebetrau, Tetsuma Kawaji, Claudio Moretti, Zenon Huczek, Shaoping Nie, Toshiharu Fujii, Luis Correia, Masa‐aki Kawashiri, Berenice Caneiro‐Queija, Rafael Cobas Paz, José María García‐Acuña, Danielle A. Southern, Emilio Alfonso, Belén Terol, Alberto Garay, Dongfeng Zhang, Yalei Chen, Ioanna Xanthopoulou, Neriman Osman, Helge Möllmann, Hiroki Shiomi, Francesca Giordana, Fiorenzo Gaita, Michał Kowara, Krzysztof J. Filipiak‬, Xiao Wang, Yan Yan, Jingyao Fan, Yuji Ikari, Takuya Nakahayshi, Kenji Sakata, Masakazu Yamagishi, Oliver Kalpak, Saško Kedev, Daniel Rivera-Asenjo, Emad Abu‐Assi

Bibliographic record

VenueInternational Journal of Cardiology · 2018
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsLibin Cardiovascular Institute of Alberta
Fundersnot available
KeywordsMedicineConventional PCIAcute coronary syndromePercutaneous coronary interventionInternal medicineFramingham Risk ScoreCohortPopulationAntithromboticSurgeryMyocardial infarctionDisease

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)0.014
metaresearch head score (Gemma)0.034
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 score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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

Citations90
Published2018
Admission routes1
Has abstractno

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