{"id":"W2998633251","doi":"10.1124/pr.116.013003","title":"Patient and Disease–Specific Induced Pluripotent Stem Cells for Discovery of Personalized Cardiovascular Drugs and Therapeutics","year":2019,"lang":"en","type":"review","venue":"Pharmacological Reviews","topic":"Pluripotent Stem Cells Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":215,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; University of Toronto","keywords":"Induced pluripotent stem cell; Drug discovery; Disease; Medicine; Clinical trial; Precision medicine; Personalized medicine; Regenerative medicine; Drug; Computational biology; Drug development; Bioinformatics; Neuroscience; Pharmacology; Stem cell; Biology; Embryonic stem cell; Internal medicine; Pathology; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007381437,0.0005804042,0.002409871,0.00007212337,0.00007376607,0.00005782801,0.0003346232,0.0003178083,0.00001218871],"category_scores_gemma":[0.00003377987,0.0003792238,0.001592856,0.0001215302,0.000194061,0.000008889624,0.0004741532,0.0002905198,0.00001082071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005033919,"about_ca_system_score_gemma":0.0001780923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.063485e-7,"about_ca_topic_score_gemma":7.230421e-8,"domain_scores_codex":[0.9963914,0.0009047232,0.0008832878,0.001014009,0.0003659661,0.000440577],"domain_scores_gemma":[0.9984624,0.0001659427,0.0004422422,0.0005266551,0.0001054644,0.0002973295],"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":[0.0001324256,0.0001277534,0.000002891359,0.02278372,0.0009535421,0.00000516905,0.00001827244,8.533755e-7,0.01367503,0.00001628812,0.0007802658,0.9615038],"study_design_scores_gemma":[0.0006618591,0.0003435173,0.000001189696,0.001509423,0.002383674,0.000005342432,0.0000133651,0.000008527821,0.001186777,0.000005765636,0.9934662,0.0004143811],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002244764,0.9908804,0.0001789784,0.00002324489,0.0002290533,0.006110653,0.0003001243,0.000006536496,0.00002619264],"genre_scores_gemma":[0.0005552297,0.9976588,0.0001124108,0.0001442693,0.0001531429,0.0008532139,0.0001464142,0.00005702237,0.0003195343],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9926859,"threshold_uncertainty_score":0.9998659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1333190733528558,"score_gpt":0.3661321435024399,"score_spread":0.2328130701495841,"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."}}