{"id":"W4321018096","doi":"10.1161/circresaha.122.321670","title":"Modeling Heart Diseases on a Chip: Advantages and Future Opportunities","year":2023,"lang":"en","type":"review","venue":"Circulation Research","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Heart and Stroke Foundation; St. Michael's Hospital; Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Disease; Induced pluripotent stem cell; Drug development; Heart disease; Drug discovery; Medicine; Neuroscience; Computer science; Bioinformatics; Computational biology; Biology; Drug; Pathology; Pharmacology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000881151,0.0008391992,0.0009680939,0.001293,0.0002084388,0.001411704,0.001062927,0.001525465,0.002646859],"category_scores_gemma":[0.0007339669,0.0004534119,0.0006677936,0.001198994,0.0005132931,0.001742762,0.0006935948,0.001710714,0.00178416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004321254,"about_ca_system_score_gemma":0.0006743663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000715439,"about_ca_topic_score_gemma":0.001006987,"domain_scores_codex":[0.9997024,0.00005409513,0.00002694858,0.00004800358,0.0001409279,0.00002758917],"domain_scores_gemma":[0.9995925,0.0002190036,0.00003714352,0.00001804914,0.0001035742,0.00002975307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005180015,0.0001118178,0.0002268224,0.01134631,0.00007268301,0.0002437902,0.000100759,0.002629516,0.01186424,0.01703306,0.01747142,0.9388478],"study_design_scores_gemma":[0.00001369109,0.0001696894,0.0004095621,0.001805975,0.00009591629,0.0011524,0.00009121829,0.001540441,0.005777858,0.006881888,0.982014,0.00004740943],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004718259,0.992415,0.003289544,0.0005235712,0.0002800878,0.000009733511,0.00002271728,0.00003728327,0.002950196],"genre_scores_gemma":[0.003057591,0.9923821,0.002479318,0.0002777609,0.0002175993,0.00002028739,0.00004645725,0.00001049862,0.001508335],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002646859,"threshold_uncertainty_score":0.008854628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3467864515153356,"score_gpt":0.4627863792732271,"score_spread":0.1159999277578915,"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."}}