{"id":"W3216512054","doi":"10.2174/1574893616666211119093100","title":"Machine Learning and Deep Learning Strategies in Drug Repositioning","year":2021,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Drug repositioning; Computer science; Drug; Drug discovery; Machine learning; Artificial intelligence; Preprocessor; Drug target; Data pre-processing; Data science; Medicine; Bioinformatics; Pharmacology","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":[0.001723246,0.0009742624,0.001277839,0.002126778,0.0004983378,0.001454101,0.001893078,0.001283642,0.002640804],"category_scores_gemma":[0.00488389,0.0004823777,0.000805142,0.002411746,0.001241426,0.003167463,0.001745968,0.002008873,0.0007374321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001500953,"about_ca_system_score_gemma":0.002092493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004308847,"about_ca_topic_score_gemma":0.004774427,"domain_scores_codex":[0.9991725,0.0002621105,0.00008739038,0.0001855417,0.0002041003,0.0000882825],"domain_scores_gemma":[0.9981843,0.001114033,0.0001827616,0.0001661767,0.0002619524,0.00009083257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001280488,0.000276507,0.00271956,0.0008911113,0.0001709195,0.000164055,0.0001392809,0.3268434,0.002562508,0.07105265,0.005480763,0.5895712],"study_design_scores_gemma":[0.00001909052,0.00007509431,0.0003296435,0.0000806413,0.00003638284,0.00008911446,0.000032446,0.9346744,0.002104004,0.05765748,0.004883377,0.00001821235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01729287,0.01069602,0.9615294,0.00248603,0.0001747339,0.0001304476,0.0002369842,0.0006539121,0.006799578],"genre_scores_gemma":[0.5718412,0.01373869,0.4047368,0.001570245,0.0003707618,0.0003608368,0.000759459,0.0001216773,0.006500333],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004308847,"threshold_uncertainty_score":0.01089019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01732519701801303,"score_gpt":0.3018280753820009,"score_spread":0.2845028783639879,"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."}}