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Record W3211964189 · doi:10.1016/j.jacbts.2021.11.001

Electroanatomical Navigation to Minimize Contrast Medium or X-Rays During Stenting

2021· article· en· W3211964189 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACC Basic to Translational Science · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de MontréalAbbott (Canada)Montreal Heart Institute
FundersAbbott VascularAbbott Laboratories
KeywordsContrast (vision)MedicineOptical coherence tomographyCarotid arteriesContrast mediumRadiologyCoronary arteriesBiomedical engineeringComputer scienceCardiologyComputer visionArtery

Abstract

fetched live from OpenAlex

Stents can be effectively implemented with no x-rays or contrast medium. Modified stents were successfully implanted in 9 of 11 attempted targets (82%) (7 carotid and 4 coronary arteries) using an impedance-sensitive navigation system and optical coherence tomography. Electroanatomical navigation systems can be used to assist interventionalists in performing arterial stenting while minimizing x-ray and contrast use, thereby potentially enhancing safety for both patients and catheterization laboratory staff members.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.780
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.292
Teacher spread0.277 · 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