{"id":"W2996036235","doi":"10.7554/elife.48890","title":"Development, calibration, and validation of a novel human ventricular myocyte model in health, disease, and drug block","year":2019,"lang":"en","type":"article","venue":"eLife","topic":"Cardiac electrophysiology and arrhythmias","field":"Medicine","cited_by":271,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Horizon 2020; BHF Centre of Research Excellence, Oxford; Partnership for Advanced Computing in Europe AISBL; National Centre for the Replacement, Refinement and Reduction of Animals in Research; European Commission; Wellcome; European Federation of Pharmaceutical Industries and Associations; Amazon Web Services; British Heart Foundation; Wellcome Trust","keywords":"Computer science; Cardiac electrophysiology; Drug development; hERG; Computational model; Neuroscience; Medicine; Electrophysiology; Drug; Artificial intelligence; Pharmacology; Internal medicine; Biology; Potassium channel","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":[0.0004943541,0.0002653145,0.0003518816,0.0001663548,0.0002073164,0.0005329032,0.0008025886,0.0009202755,0.001551749],"category_scores_gemma":[0.001336277,0.0001372464,0.0004637091,0.0001452939,0.0003557584,0.0002716978,0.0005693918,0.0005497946,0.0002773233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000347064,"about_ca_system_score_gemma":0.001000932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003207971,"about_ca_topic_score_gemma":0.002515465,"domain_scores_codex":[0.9998664,0.00003920876,0.00001058071,0.00002720048,0.00003860603,0.00001795986],"domain_scores_gemma":[0.9996241,0.000194426,0.00002818082,0.00004574953,0.00007516649,0.00003234822],"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":[0.0001259455,0.00007558631,0.002399251,0.0001339914,0.00003822995,0.0002149589,0.0001147762,0.9537891,0.02238554,0.005700822,0.001218782,0.01380309],"study_design_scores_gemma":[0.00002444994,0.00009194073,0.0005912154,0.00001724975,0.00001418452,0.00006310618,0.0000222532,0.9897132,0.005186836,0.001234034,0.003029878,0.00001169086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4794393,0.0008405254,0.4958564,0.001041757,0.0002584147,0.0002387538,0.002079192,0.00102114,0.01922454],"genre_scores_gemma":[0.932419,0.0004325088,0.06274512,0.000170317,0.00002417532,0.0002601698,0.0007726909,0.0001156891,0.003060396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003207971,"threshold_uncertainty_score":0.006378591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01251121133185087,"score_gpt":0.2634398673557004,"score_spread":0.2509286560238495,"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."}}