{"id":"W2001514009","doi":"10.1016/s0092-8674(03)01070-5","title":"Old Drugs, New Tricks","year":2004,"lang":"en","type":"review","venue":"Cell","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biology; Computational biology; Mode of action; Action (physics); Drug discovery; Bioinformatics; Toxicology","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":[0.001846271,0.001665449,0.002452706,0.003391066,0.000562034,0.002371788,0.002476987,0.00274751,0.004485075],"category_scores_gemma":[0.003096385,0.0006169604,0.0005967547,0.003774522,0.002805129,0.004415935,0.001067705,0.00477619,0.004020303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001461128,"about_ca_system_score_gemma":0.001718245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001724089,"about_ca_topic_score_gemma":0.003616195,"domain_scores_codex":[0.9993263,0.0001966052,0.00005056771,0.00009493154,0.0002998772,0.0000317681],"domain_scores_gemma":[0.9977288,0.001508489,0.0001278229,0.0001143282,0.0004082946,0.0001122461],"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":[0.00007714626,0.00007882569,0.0002271927,0.007937775,0.0001267012,0.0001940884,0.00006634492,0.001056748,0.0005401399,0.04162108,0.1587065,0.7893674],"study_design_scores_gemma":[0.00003633694,0.0000293816,0.0001672015,0.001610124,0.00004777904,0.0007929408,0.00004090996,0.0004831171,0.0002365199,0.0215717,0.9749658,0.00001811901],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000918822,0.9916303,0.001716834,0.002649187,0.0010993,0.000008330552,0.00002067707,0.00002754721,0.00275604],"genre_scores_gemma":[0.00120491,0.9912978,0.001962827,0.002001339,0.001391559,0.00002129407,0.00004536353,0.000009652376,0.002065219],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004485075,"threshold_uncertainty_score":0.01500404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05078252701873616,"score_gpt":0.3480504428633237,"score_spread":0.2972679158445875,"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."}}