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Record W2941487989 · doi:10.1016/j.rec.2019.02.013

Left atrial appendage occlusion for stroke despite oral anticoagulation (resistant stroke). Results from the Amplatzer Cardiac Plug registry

2019· article· es· W2941487989 on OpenAlexaff
Ignacio Cruz‐González, Rocío González-Ferreiro, Xavier Freixa, Sameer Gafoor, Samera Shakir, Heyder Omran, Sérgio Berti, Gennaro Santoro, Joëlle Kefer, Ulf Landmesser, Jens Erik Nielsen‐Kudsk, Prapa Kanagaratnam, Fabian Nietlispach, Steffen Gloekler, Adel Aminian, Paolo Danna, Marco Rezzaghi, Friederike Stock, Miroslava Stolcova, Luís Paiva, Marco A. Costa, Xavier Millán, Réda Ibrahim, Tobias Tichelbäcker, Wolfgang Schillinger, Jai‐Wun Park, Horst Sievert, Bernhard Meier, Apostolos Tzikas

Bibliographic record

VenueRevista Española de Cardiología (English Edition) · 2019
Typearticle
Languagees
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMontreal Heart Institute
FundersNovo Nordisk Fonden
KeywordsMedicineCardiologyStroke (engine)OcclusionLeft atrial appendage occlusionInternal medicineAtrial fibrillationAtrial AppendageAppendageWarfarinAnatomy

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)0.001
metaresearch head score (Gemma)0.003
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.026
GPT teacher head0.290
Teacher spread0.264 · 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

Citations36
Published2019
Admission routes1
Has abstractno

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