{"id":"W4242807744","doi":"10.1515/iupac.83.0430","title":"Partial Agonist","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Computer science; Multidisciplinary approach; Field (mathematics); Process (computing); Data science; Management science; Engineering; Sociology; Biology; Linguistics; Mathematics","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":[0.0009878098,0.001615045,0.001705219,0.001513753,0.001057905,0.002539865,0.002508176,0.001733767,0.1530713],"category_scores_gemma":[0.00560642,0.0004927377,0.001609117,0.002839352,0.000386933,0.001652478,0.00173789,0.002308097,0.1671442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00120726,"about_ca_system_score_gemma":0.002519866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009658286,"about_ca_topic_score_gemma":0.02246545,"domain_scores_codex":[0.9988583,0.0001761749,0.0001614998,0.0003949809,0.0002446751,0.0001643033],"domain_scores_gemma":[0.9982016,0.000406349,0.0001933453,0.0006030825,0.000403865,0.0001916694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004104255,0.00005211875,0.001908055,0.0009164048,0.0000482119,0.00006648123,0.0000205055,0.0002451987,0.0001780751,0.0008408669,0.9850755,0.01023817],"study_design_scores_gemma":[0.0003382513,0.0000652416,0.005101214,0.0004293877,0.00006531736,0.0003632754,0.00008494757,0.0003177389,0.0004941039,0.002456281,0.9902534,0.00003090017],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007113307,0.0004426571,0.0002520107,0.0002363641,0.00007295076,0.00004564719,0.9920528,0.0005190003,0.005667225],"genre_scores_gemma":[0.001989338,0.0003808403,0.0005630093,0.0003904756,0.00002530481,0.0001811573,0.9922222,0.00009711321,0.004150414],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1530713,"threshold_uncertainty_score":0.5120745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02233397020385392,"score_gpt":0.4296144524370124,"score_spread":0.4072804822331585,"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."}}