MétaCan
Menu
Back to cohort
Record W1986743901 · doi:10.1002/ccd.1175

Characterization of ultrasound‐detected cerebral microemboli in patients undergoing cardiac catheterization using an in vitro middle cerebral artery model

2001· article· en· W1986743901 on OpenAlexaff
Yi Yang, Donald G. Grosset, Tao Yang, Kennedy R. Lees

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2001
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineCardiac catheterizationTranscranial DopplerMiddle cerebral arteryCatheterCardiologyInternal medicineEmbolizationDoppler effectCerebral arteriesRadiologyUltrasoundIschemia

Abstract

fetched live from OpenAlex

Cerebral embolization has been documented as one of the complications of diagnostic heart catheterization by transcranial Doppler (TCD). This study aimed to evaluate our hypothesis that the nature of embolic signals involved in different stages of catheter manipulation may be distinct. TCD-detected cerebral emboli occurring at different phases of cardiac catheterization were registered and differentiated by comparing their acoustic signatures with the Doppler signals generated from clinically frequently encountered embolic materials in an in vitro middle cerebral artery model. We found that there was a significant difference in embolic signal intensity and duration between different phases of cardiac catheterization. Our data suggest that different types of emboli may be involved in different phases of the catheterization. Cathet Cardiovasc Intervent 2001;53:323-330.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.244
Teacher spread0.218 · 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 designSimulation or modeling
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

Citations3
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCatheterization and Cardiovascular InterventionsSame topicCerebrovascular and Carotid Artery DiseasesFrench-language works237,207