{"id":"W1528082181","doi":"10.6000/1927-5129.2015.11.59","title":"Personalized Medicines: Reforming Diagnostics and Therapeutics","year":2015,"lang":"en","type":"article","venue":"Journal of Basic & Applied Sciences","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Personalized medicine; Medicine; Precision medicine; Alternative medicine; Pharmacology; Bioinformatics; Biology; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.01153432,0.000841527,0.001188177,0.002437507,0.001483458,0.007792682,0.001532454,0.006447413,0.006046891],"category_scores_gemma":[0.0119057,0.0004288813,0.0006430942,0.001980853,0.01457022,0.01663152,0.005436162,0.007922996,0.002443725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006246567,"about_ca_system_score_gemma":0.007156077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001807309,"about_ca_topic_score_gemma":0.001567074,"domain_scores_codex":[0.9917399,0.004310712,0.0003723828,0.0008355623,0.002265794,0.0004756956],"domain_scores_gemma":[0.9927657,0.003905723,0.0005802331,0.0009561916,0.00124136,0.0005508154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005410059,0.00008265798,0.0005338671,0.0006786475,0.00003531661,0.0001269575,0.0006258228,0.001342719,0.0006780246,0.8451607,0.02980787,0.1208734],"study_design_scores_gemma":[0.00002740968,0.0001093171,0.0004855577,0.0007713201,0.00002484779,0.0002691261,0.0006210609,0.001623007,0.0008401479,0.5628244,0.4323666,0.0000371692],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.007318429,0.2439986,0.1038877,0.5231723,0.008735837,0.000198495,0.0003295326,0.0006141408,0.1117449],"genre_scores_gemma":[0.3333346,0.3354687,0.1419518,0.1335885,0.02249749,0.0003747514,0.0003660158,0.000397026,0.03202112],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01153432,"threshold_uncertainty_score":0.06100005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06948738707635548,"score_gpt":0.3403330237765729,"score_spread":0.2708456367002174,"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."}}