{"id":"W4387417530","doi":"10.5267/j.ccl.2023.8.001","title":"Current trends of chemoinformatics and computer chemistry in drug design: A review","year":2023,"lang":"en","type":"review","venue":"Current Chemistry Letters","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education and Science of Ukraine","keywords":"Cheminformatics; Chemistry; Biochemical engineering; In silico; Management science; Nanotechnology; Combinatorial chemistry; Computational chemistry; Biochemistry; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001102907,0.001058109,0.001463911,0.003095831,0.0003243313,0.001416897,0.001206743,0.001277997,0.004666566],"category_scores_gemma":[0.001551397,0.0004016125,0.0005617003,0.004860481,0.0007535,0.002075197,0.0008177184,0.002249254,0.003601508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007112494,"about_ca_system_score_gemma":0.001800688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009685806,"about_ca_topic_score_gemma":0.001526783,"domain_scores_codex":[0.999617,0.00008480604,0.00004861217,0.00005646553,0.0001634235,0.00002972135],"domain_scores_gemma":[0.9984813,0.0009817143,0.0001032836,0.00004049118,0.000294454,0.00009872863],"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":[0.0000579606,0.0001004066,0.0001946228,0.01802378,0.00008364629,0.0001168695,0.00005737129,0.001067596,0.001239515,0.008700701,0.03026263,0.9400949],"study_design_scores_gemma":[0.00002462887,0.0001377893,0.0005048274,0.0045473,0.0001089575,0.0008081471,0.00005401953,0.0006127911,0.0007193902,0.006091509,0.9863528,0.00003799524],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001206799,0.9968087,0.0008899395,0.0004394402,0.0003034951,0.000007848533,0.00001873135,0.00001815448,0.001393022],"genre_scores_gemma":[0.0005542656,0.9976745,0.0008832514,0.0002203473,0.0002925518,0.000009208751,0.00002857186,0.000003788903,0.0003335201],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004666566,"threshold_uncertainty_score":0.01561123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08781371682607429,"score_gpt":0.3806967584902867,"score_spread":0.2928830416642124,"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."}}