{"id":"W4251781122","doi":"10.26434/chemrxiv.14572050.v1","title":"De Novo Design with Deep Generative Models Based on 3D Similarity Scoring","year":2021,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"AstraZeneca (Canada)","funders":"","keywords":"Pharmacophore; Similarity (geometry); Chemical space; Context (archaeology); Artificial intelligence; Generative grammar; Computer science; Orthogonality; Generative model; Machine learning; Quantitative structure–activity relationship; Mathematics; Bioinformatics; Drug discovery; Biology","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":[0.0009625752,0.0006127885,0.0007806151,0.00043424,0.0002498695,0.0007401024,0.0009628063,0.0009893926,0.002493187],"category_scores_gemma":[0.001742893,0.0006608246,0.001241683,0.0004395707,0.0008581902,0.0006185091,0.00107737,0.001242821,0.0005575074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007218884,"about_ca_system_score_gemma":0.000894781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002583429,"about_ca_topic_score_gemma":0.003841283,"domain_scores_codex":[0.9996822,0.00009942379,0.00001503559,0.00005498427,0.0001093722,0.00003901461],"domain_scores_gemma":[0.9992476,0.0004500846,0.0000693179,0.0001051138,0.00008386594,0.00004410995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002339753,0.00002430187,0.0002750093,0.00002855833,0.00002195724,0.00004819294,0.0000224908,0.9727243,0.002085208,0.009288679,0.0002245937,0.01523334],"study_design_scores_gemma":[0.00000523088,0.00001787809,0.00001733306,0.000002712265,0.000003666637,0.000008143832,0.000001429813,0.9962341,0.0005375042,0.002863697,0.0003054564,0.000002822591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02877213,0.0002260416,0.9668508,0.000165217,0.00003334362,0.0000558928,0.00007054766,0.0005150462,0.003311015],"genre_scores_gemma":[0.6249807,0.0002996907,0.3694073,0.0002502861,0.00003167278,0.0002642045,0.0002995607,0.0002406133,0.004225916],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002583429,"threshold_uncertainty_score":0.008340478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08735537391331043,"score_gpt":0.3060896658001475,"score_spread":0.2187342918868371,"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."}}