{"id":"W2062565671","doi":"10.1007/s00280-014-2433-9","title":"DrugPath: a database for academic investigators to match oncology molecular targets with drugs in development","year":2014,"lang":"en","type":"article","venue":"Cancer Chemotherapy and Pharmacology","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Spinal Cord Injury BC; BC Cancer Agency","funders":"","keywords":"Drug development; Identification (biology); Anticancer drug; Computational biology; Drug; Drug discovery; Molecular oncology; Medicine; Database; Bioinformatics; Pharmacology; Cancer; Computer science; Biology; Internal medicine","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":[0.002116482,0.001213768,0.001495927,0.00662022,0.0005142346,0.002047688,0.002599286,0.001388195,0.04006215],"category_scores_gemma":[0.01418241,0.0006824255,0.001018384,0.007023532,0.0003152809,0.001830931,0.00181355,0.001273308,0.01332361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000898357,"about_ca_system_score_gemma":0.003383375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002598271,"about_ca_topic_score_gemma":0.003606426,"domain_scores_codex":[0.9993837,0.000136594,0.0001292568,0.0001450504,0.0001583356,0.0000470495],"domain_scores_gemma":[0.993721,0.00312461,0.0008020844,0.001171844,0.0006150252,0.0005654601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002135851,0.0004086414,0.01410364,0.002959866,0.0006218918,0.0005637066,0.00014707,0.008316886,0.003544159,0.01849592,0.7908633,0.1578391],"study_design_scores_gemma":[0.001652429,0.0002512377,0.006731213,0.0004795862,0.00084695,0.001446191,0.0001723114,0.03376835,0.00845387,0.02868614,0.9173821,0.0001295743],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.01474004,0.004800371,0.0740126,0.00315938,0.0003930707,0.0008177871,0.808759,0.06816938,0.02514835],"genre_scores_gemma":[0.09243499,0.007280077,0.1136384,0.002799335,0.0002477988,0.001730904,0.7694592,0.005853284,0.00655602],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04006215,"threshold_uncertainty_score":0.1340213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02397433063411096,"score_gpt":0.3680921221212126,"score_spread":0.3441177914871016,"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."}}