{"id":"W2052436426","doi":"10.1016/s1359-6446(01)02096-7","title":"The dynamics of molecular networks: applications to therapeutic discovery","year":2001,"lang":"en","type":"article","venue":"Drug Discovery Today","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kingston Process Metallurgy (Canada)","funders":"","keywords":"Drug discovery; Identification (biology); Computational biology; Drug; Personalized medicine; Genomics; Computer science; Medicine; Data science; Bioinformatics; Pharmacology; Biology; Genome","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":[0.0009615829,0.000896165,0.001275743,0.001515208,0.0008318682,0.002059666,0.00124483,0.001827603,0.002710835],"category_scores_gemma":[0.007677796,0.0005977038,0.0007505678,0.002199715,0.00303708,0.004348823,0.001567979,0.002226494,0.0004170851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001311017,"about_ca_system_score_gemma":0.001052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00355561,"about_ca_topic_score_gemma":0.002637012,"domain_scores_codex":[0.9996669,0.0001205992,0.00001228452,0.00006750975,0.0001097925,0.000022892],"domain_scores_gemma":[0.9970738,0.002165484,0.000298489,0.0001294969,0.0001319408,0.0002008489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005791586,0.00004432169,0.001214154,0.0003042386,0.0000531702,0.00005781024,0.0001224585,0.436207,0.001324769,0.5184015,0.003666369,0.03854637],"study_design_scores_gemma":[0.0000228114,0.00001411425,0.0002447804,0.00002908805,0.00001300898,0.00003695886,0.00002823452,0.560113,0.0002519805,0.4324318,0.006798638,0.00001558748],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03991684,0.04079461,0.8878895,0.01101559,0.001121146,0.00007755483,0.0005538116,0.0005076191,0.01812341],"genre_scores_gemma":[0.6876583,0.09238776,0.2049567,0.0009791445,0.00273705,0.0004729084,0.0005935468,0.0002760354,0.009938532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00355561,"threshold_uncertainty_score":0.009512126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111843575343464,"score_gpt":0.2804502025134616,"score_spread":0.269331766760027,"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."}}