{"id":"W4378498767","doi":"10.48550/arxiv.2305.15453","title":"Drugst.One -- A plug-and-play solution for online systems medicine and network-based drug repurposing","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación; National Institute of Diabetes and Digestive and Kidney Diseases; Staatssekretariat für Bildung, Forschung und Innovation; European Commission; Natural Sciences and Engineering Research Council of Canada; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft","keywords":"Repurposing; Drug repositioning; Computer science; Data science; Drug discovery; Plug-in; Systems medicine; Process (computing); Systems biology; Biological network; Software; Adaptability; Software engineering; Drug; Engineering; Bioinformatics; Medicine; Pharmacology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002165562,0.001963787,0.001126733,0.001906616,0.0006038357,0.002050094,0.003300475,0.001263041,0.05285826],"category_scores_gemma":[0.005309163,0.001357832,0.002024408,0.000961267,0.0008840304,0.003402349,0.004264191,0.00257221,0.02704527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174428,"about_ca_system_score_gemma":0.001679458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001815697,"about_ca_topic_score_gemma":0.002488312,"domain_scores_codex":[0.9992092,0.0001251146,0.00006246762,0.0001686404,0.0003225658,0.0001121242],"domain_scores_gemma":[0.9980034,0.0008712396,0.00011957,0.0003893032,0.0002374118,0.0003789852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00260577,0.0006753848,0.00464327,0.001999933,0.0005737022,0.001770267,0.000563829,0.01901096,0.01622785,0.03381436,0.6508124,0.2673023],"study_design_scores_gemma":[0.002050609,0.0002993188,0.003725265,0.0004423619,0.0001919632,0.001591406,0.0001504542,0.2655708,0.03556508,0.06951994,0.6204979,0.0003948183],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.004770242,0.0009744331,0.3378368,0.001204113,0.000559301,0.0005993169,0.01481725,0.6228524,0.01638602],"genre_scores_gemma":[0.1577472,0.004415339,0.4823137,0.004707647,0.0005421078,0.00281578,0.09724267,0.1999172,0.05029837],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.05285826,"threshold_uncertainty_score":0.1768285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0671258993797184,"score_gpt":0.2086725659776056,"score_spread":0.1415466665978872,"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."}}