{"id":"W4237739054","doi":"10.1515/iupac.83.0408","title":"Lead Optimization","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; Field (mathematics); Process (computing); Multidisciplinary approach; Data science; Component (thermodynamics); Management science; Engineering; Sociology; Biology; Linguistics; Mathematics; Social science","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":[0.001821789,0.002913272,0.002628965,0.00287506,0.001086497,0.003177894,0.003963354,0.001740546,0.0965744],"category_scores_gemma":[0.008068805,0.0006886576,0.003374888,0.003767339,0.0004224479,0.001672089,0.001621431,0.002565745,0.1007176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001671879,"about_ca_system_score_gemma":0.003255219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007948978,"about_ca_topic_score_gemma":0.02762893,"domain_scores_codex":[0.9979752,0.0003139844,0.0003064747,0.0007006066,0.0004877911,0.0002159612],"domain_scores_gemma":[0.9976279,0.0007314506,0.0002176133,0.0008268578,0.0004669617,0.0001293021],"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":[0.0003615407,0.000105545,0.002419005,0.001839796,0.0001178237,0.00007169044,0.00002217861,0.002924909,0.0002801881,0.001829268,0.9670088,0.02301934],"study_design_scores_gemma":[0.0007620425,0.0001302889,0.004026982,0.0008040043,0.000189452,0.0004013515,0.00006946802,0.006443362,0.001797135,0.007469506,0.9778352,0.0000712003],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001316754,0.0009759667,0.001352122,0.0001840073,0.0001071159,0.0001437306,0.9864053,0.00226923,0.007245707],"genre_scores_gemma":[0.002385733,0.0004060149,0.002947754,0.0001621273,0.00001748446,0.000278503,0.9909802,0.0002620243,0.002560069],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0965744,"threshold_uncertainty_score":0.3230736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0206692872712931,"score_gpt":0.4220234484900751,"score_spread":0.401354161218782,"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."}}