{"id":"W4303647035","doi":"10.1113/jp283817","title":"Determinants and therapeutic potential of calcium handling abnormalities in atrial fibrillation: what can we learn from computer models?","year":2022,"lang":"en","type":"article","venue":"The Journal of Physiology","topic":"Cardiac electrophysiology and arrhythmias","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"National Institutes of Health; European Commission","keywords":"Proarrhythmia; Atrial fibrillation; Medicine; Cardiac electrophysiology; Cardiology; Sudden cardiac death; Neuroscience; Internal medicine; Electrophysiology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001656547,0.0009897324,0.001551462,0.000696685,0.000391498,0.002805451,0.00192204,0.002704617,0.004767818],"category_scores_gemma":[0.01180401,0.0005503684,0.001277539,0.0004526117,0.001966965,0.004493266,0.001500761,0.004070035,0.001310644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007662121,"about_ca_system_score_gemma":0.001313819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004017232,"about_ca_topic_score_gemma":0.002311975,"domain_scores_codex":[0.9995521,0.0002070632,0.00002927893,0.00006320854,0.0001002857,0.00004794356],"domain_scores_gemma":[0.9941158,0.004557789,0.0002226547,0.0003419817,0.0004933595,0.0002683211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005045662,0.0004856551,0.01247958,0.004009923,0.0005390978,0.0007143043,0.0007631034,0.4018151,0.003157614,0.2421416,0.03797234,0.2954171],"study_design_scores_gemma":[0.00009619504,0.0003265339,0.002176293,0.001749947,0.0001982789,0.0004009639,0.0004392379,0.383301,0.001147909,0.541281,0.06871801,0.0001645814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0965252,0.3379164,0.3385887,0.168802,0.003961635,0.0001591157,0.001974689,0.001763277,0.05030899],"genre_scores_gemma":[0.6304398,0.2895765,0.059943,0.007911845,0.003587786,0.000329769,0.001226906,0.0004572534,0.006527086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004767818,"threshold_uncertainty_score":0.0159499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02140977522191658,"score_gpt":0.2658921820119308,"score_spread":0.2444824067900142,"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."}}