{"id":"W2098318720","doi":"10.1186/gm326","title":"Drug repositioning for personalized medicine","year":2012,"lang":"en","type":"review","venue":"Genome Medicine","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":255,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Drug repositioning; Personalized medicine; Medicine; Drug discovery; Precision medicine; Pharmacogenomics; Clinical trial; Disease; Drug; Drug development; Bioinformatics; Computational biology; Pharmacology; Biology; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001027028,0.0004965268,0.001459574,0.0001273862,0.0001684107,0.00001020238,0.0003768826,0.0003816701,0.0002391096],"category_scores_gemma":[0.00008022733,0.0003407823,0.0003346434,0.0001424194,0.000319934,0.000002952593,0.0001221984,0.0002380047,0.00002820188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005279734,"about_ca_system_score_gemma":0.0001194422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001122834,"about_ca_topic_score_gemma":0.000004253197,"domain_scores_codex":[0.9978611,0.00007258738,0.0009258944,0.00042794,0.00019776,0.0005146522],"domain_scores_gemma":[0.9983816,0.00006818549,0.0005830112,0.0006197992,0.0001098015,0.0002375802],"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":[0.00004207107,0.00002935613,9.919602e-7,0.01344783,0.0006844399,0.000003711589,0.0006066213,0.000001455891,0.000245226,0.001127247,0.04200342,0.9418076],"study_design_scores_gemma":[0.0007667964,0.0002412021,6.603175e-7,0.002718701,0.001337274,0.0001398545,0.00008714356,0.000004860082,0.000001587218,0.00008840886,0.9942546,0.0003588913],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000179242,0.9870338,0.006888132,0.0003056883,0.0008691024,0.00103634,0.00005672576,0.0000185849,0.003789857],"genre_scores_gemma":[0.00001904347,0.9735512,0.0008433039,0.0004939061,0.008307408,0.0002233418,0.005385411,0.00008714668,0.01108931],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9522512,"threshold_uncertainty_score":0.9999044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0383589223628604,"score_gpt":0.3164869214553351,"score_spread":0.2781279990924747,"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."}}