{"id":"W2055205760","doi":"10.2196/resprot.2315","title":"The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions","year":2013,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Carleton University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Universidad Politécnica de Madrid; Canarie; Microsoft Research; Heart and Stroke Foundation of Canada","keywords":"World Wide Web; Computer science; Web page; Personally identifiable information; JavaScript; Workflow; Web application; Plug-in; Internet privacy; Database; Computer security","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.001731662,0.001231691,0.0007433525,0.002906374,0.0003767889,0.001724017,0.001224762,0.000884944,0.02068737],"category_scores_gemma":[0.003992906,0.0005898752,0.0005619036,0.0009121972,0.0003752262,0.002581093,0.002358753,0.0008088936,0.007816925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007428359,"about_ca_system_score_gemma":0.001455784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003143103,"about_ca_topic_score_gemma":0.005427152,"domain_scores_codex":[0.9993588,0.0001213225,0.00007036854,0.0001737756,0.0002331756,0.00004251813],"domain_scores_gemma":[0.9979862,0.0009676194,0.0002023146,0.0002892848,0.0002694264,0.0002850896],"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":[0.004430928,0.0008470449,0.02624218,0.002316634,0.0004264412,0.001506142,0.002945325,0.002108322,0.04358156,0.009550066,0.3892179,0.5168275],"study_design_scores_gemma":[0.001546402,0.001025884,0.03798215,0.0008980745,0.0006023215,0.003705874,0.001278538,0.1640243,0.06365097,0.02315834,0.7014209,0.0007061782],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"software","genre_gemma":"protocol","genre_scores_codex":[0.03534991,0.00160594,0.216481,0.001334715,0.0001911895,0.00196815,0.04403201,0.6690782,0.02995895],"genre_scores_gemma":[0.3098527,0.002231633,0.5671874,0.002712743,0.0003204696,0.001810455,0.06632612,0.01274613,0.03681225],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.02068737,"threshold_uncertainty_score":0.06920618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2335661848216555,"score_gpt":0.5180854587097071,"score_spread":0.2845192738880516,"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."}}