{"id":"W2913124902","doi":"10.1093/cvr/cvz039","title":"In vivo ratiometric optical mapping enables high-resolution cardiac electrophysiology in pig models","year":2019,"lang":"en","type":"article","venue":"Cardiovascular Research","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Esri (Canada)","funders":"Fogarty International Center; European Commission; European Regional Development Fund; Fundación Interhospitalaria para la Investigación Cardiovascular; National Institute of Biomedical Imaging and Bioengineering; University of Connecticut; Ministerio de Ciencia, Innovación y Universidades; Centro Nacional de Investigaciones Cardiovasculares; Agence Nationale de la Recherche; National Institutes of Health; Sociedad Española de Cardiología; Instituto de Salud Carlos III; European Research Area Network on Cardiovascular Diseases","keywords":"Optical mapping; Ex vivo; In vivo; Biomedical engineering; Electrophysiology; Voltage-sensitive dye; Optical recording; Preclinical imaging; Materials science; Biophysics; Chemistry; Medicine; Cardiology; Internal medicine; Biology; Optoelectronics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003323762,0.0001691934,0.0008563301,0.002013861,0.00005321822,0.00004342478,0.000184662,0.0002205542,0.00006197974],"category_scores_gemma":[0.0004385451,0.0001558861,0.0004107937,0.002949937,0.0001750815,0.0002082271,0.0001502339,0.001119974,0.00009762865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000647867,"about_ca_system_score_gemma":0.0001992228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007562342,"about_ca_topic_score_gemma":0.000003112266,"domain_scores_codex":[0.9964632,0.000596831,0.0003246916,0.0006318814,0.001007489,0.0009759345],"domain_scores_gemma":[0.9985231,0.0002202862,0.00001503475,0.0008360207,0.0002579813,0.0001475459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005021419,0.0005310514,0.00578946,0.0006004516,0.0008406754,0.0007358638,0.0002516129,0.004586242,0.9414952,0.03618762,0.00252521,0.005954415],"study_design_scores_gemma":[0.01362043,0.004684773,0.07507509,0.001604063,0.0003651648,0.000272635,0.001160587,0.1515428,0.6561059,0.05262681,0.0407082,0.002233603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9723648,0.007056301,0.006393184,0.0006162793,0.0001236353,0.001314896,0.000002603617,0.00009589888,0.01203244],"genre_scores_gemma":[0.9927992,0.001469779,0.004693775,0.00004975094,0.0001762744,0.0001466554,0.00001106048,0.0000369152,0.0006166456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2853894,"threshold_uncertainty_score":0.6356851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04481802666471067,"score_gpt":0.3400622895618554,"score_spread":0.2952442628971447,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}