{"id":"W3154922863","doi":"10.1038/s41598-021-97871-7","title":"Deep mutational scanning of the plasminogen activator inhibitor-1 functional landscape","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Protease and Inhibitor Mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Thrombosis and Atherosclerosis Research Institute","funders":"National Heart, Lung, and Blood Institute; Hamilton Health Sciences; American Society of Hematology; National Institutes of Health; National Hemophilia Foundation; National Institute of General Medical Sciences; American Heart Association; Howard Hughes Medical Institute","keywords":"Plasminogen activator inhibitor-1; Computational biology; Biology; Computer science; Bioinformatics; Plasminogen activator; Genetics","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":[0.0003260684,0.000388838,0.0003860719,0.0002924923,0.0002037682,0.0003673119,0.0002629619,0.0002949414,0.0009950792],"category_scores_gemma":[0.0005132677,0.0001536109,0.0002848447,0.0003471958,0.0001937788,0.00017778,0.000386214,0.0006204362,0.0002311167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003319245,"about_ca_system_score_gemma":0.0001984673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004553934,"about_ca_topic_score_gemma":0.000851506,"domain_scores_codex":[0.9998176,0.00003531365,0.00001094001,0.00004955406,0.00005374109,0.0000328723],"domain_scores_gemma":[0.9997868,0.0001013244,0.00003446268,0.00003039358,0.00002456467,0.00002255091],"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":[0.0001019992,0.00003855852,0.00120825,0.00007014074,0.00002744078,0.0001330776,0.00003886783,0.002473645,0.9883256,0.0002937446,0.0001109332,0.007177738],"study_design_scores_gemma":[0.00003398933,0.0006453434,0.01573753,0.00001869592,0.000132274,0.001274053,0.0001021424,0.03806334,0.9388024,0.0009161602,0.004237209,0.00003676367],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803082,0.0005635698,0.01672037,0.00008011814,0.00001511358,0.00003427504,0.0007094186,0.0002397588,0.001329175],"genre_scores_gemma":[0.9857548,0.000392492,0.01218757,0.00006583372,0.000004727139,0.00002860585,0.0007942981,0.00006823683,0.0007034509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009950792,"threshold_uncertainty_score":0.00332886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009802321373390058,"score_gpt":0.2171728423199447,"score_spread":0.2073705209465547,"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."}}