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Evaluating Therapies to Prevent Future Stroke in Patients with Patent Foramen Ovale-Related Strokes – The SCOPE Study

2023· report· en· W4362737762 on OpenAlexaff
David M. Kent, Jeffrey L. Saver, Scott E. Kasner, Jason Nelson, Andy Wang, Raveendhara R. Bannuru, John M. Carroll, Gilles Châtellier, Geneviève Dérumeaux, Anthony J. Furlan, Howard C. Herrmann, Peter Jüni, Jong Kim, Benjamin Koethe, Pil Hyung Lee, Bénédicte Lefebvre, Heinrich P. Mattle, Bernhard Meier, Mark Reisman, Richard W. Smalling, Lars Soendergaard, Jae‐Kwan Song, Jean‐Louis Mas, David E. Thaler

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsPatent foramen ovaleMedicineScope (computer science)Stroke (engine)Foramen ovale (heart)CardiologyInternal medicineComputer scienceEngineering

Abstract

fetched live from OpenAlex

What was the research about?A patent foramen ovale, or PFO, is a small hole between the top two chambers of the heart that didn't close correctly after birth.PFOs can raise the risk for stroke.For adults ages 18-60, about 10 percent of strokes caused by a blocked artery are related to a PFO.Among these patients, questions remain about what treatment works best to prevent future strokes. How can people use the results?Patients who had a PFO-related stroke and their doctors can use these results when considering treatments for preventing future strokes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.006
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.110
GPT teacher head0.370
Teacher spread0.260 · 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
Published2023
Admission routes1
Has abstractyes

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