{"id":"W2010630721","doi":"10.1016/j.compbiolchem.2004.11.003","title":"Assessment of chemical libraries for their druggability","year":2005,"lang":"en","type":"article","venue":"Computational Biology and Chemistry","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; McGill University; Montreal General Hospital; Université du Québec à Montréal","funders":"National Natural Science Foundation of China","keywords":"Druggability; Virtual screening; Metric (unit); Function (biology); Computer science; Chemical database; Rank (graph theory); Drug discovery; Data mining; Computational biology; Information retrieval; Chemistry; Bioinformatics; Mathematics; Biology; Biochemistry; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002320493,0.00009617556,0.0001571514,0.00001660228,0.00004823933,0.00002249927,0.0002792566,0.00007568076,0.000013275],"category_scores_gemma":[0.00007145648,0.00008621233,0.00005889703,0.00007752241,0.0001989672,0.0001461305,0.000178595,0.00007414379,4.05342e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002029473,"about_ca_system_score_gemma":0.0001688449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.618231e-7,"about_ca_topic_score_gemma":3.082722e-8,"domain_scores_codex":[0.9992778,0.0000370405,0.0002211952,0.000284965,0.0000656335,0.0001133201],"domain_scores_gemma":[0.9984464,0.00118004,0.00008717796,0.000136534,0.0001045321,0.00004530409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003429855,0.0003446198,0.009551397,0.000219804,0.0001170499,3.552119e-7,0.0003128127,0.0384443,0.0648188,0.7925678,0.0003995089,0.09318929],"study_design_scores_gemma":[0.0003864892,0.0000212942,0.01070775,0.000007508369,0.000004172968,0.0000102043,0.00001110633,0.5535616,0.05952428,0.3746434,0.0009911214,0.000131145],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3999649,0.0001469824,0.5981814,0.0009566337,0.00003294291,0.00006558197,0.00003356785,0.00003143011,0.0005865697],"genre_scores_gemma":[0.6888969,0.000001252134,0.3108509,0.0001057181,0.00005932562,0.00001368029,0.00006145654,0.000002191949,0.000008568119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5151173,"threshold_uncertainty_score":0.3515637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01758096119271337,"score_gpt":0.32629576203244,"score_spread":0.3087148008397267,"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."}}