{"id":"W2905320799","doi":"10.1016/j.isci.2018.12.003","title":"EDEn–Electroceutical Design Environment: Ion Channel Tissue Expression Database with Small Molecule Modulators","year":2018,"lang":"en","type":"article","venue":"iScience","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; Allen Discovery Center; National Institute of Arthritis and Musculoskeletal and Skin Diseases; G. Harold and Leila Y. Mathers Charitable Foundation; Templeton World Charity Foundation; Allard Foundation; W. M. Keck Foundation; National Institutes of Health; National Science Foundation","keywords":"Ion channel; Small molecule; Computer science; Interface (matter); Nanotechnology; Cancer therapy; Regenerative medicine; Bioinformatics; Computational biology; Chemistry; Materials science; Biology; Cancer; Molecule; Cell; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00116607,0.00196384,0.001379692,0.00145097,0.0002937734,0.001595724,0.002358824,0.001115037,0.02756681],"category_scores_gemma":[0.002296671,0.0008075648,0.001050688,0.001348734,0.0002756494,0.001320612,0.00108133,0.0008964891,0.01160289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006611349,"about_ca_system_score_gemma":0.001013402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008122467,"about_ca_topic_score_gemma":0.001459985,"domain_scores_codex":[0.9995742,0.00006711667,0.00008337039,0.00009425011,0.0001478439,0.00003312803],"domain_scores_gemma":[0.9993444,0.0003404557,0.00008044665,0.00009441355,0.000101397,0.00003887212],"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":[0.004129752,0.0006081809,0.003818482,0.01406748,0.0006038484,0.002269905,0.000415662,0.05160685,0.1141003,0.03302539,0.469827,0.3055271],"study_design_scores_gemma":[0.0008971,0.0002483518,0.001712051,0.0003806035,0.0001820092,0.0009472372,0.00005313729,0.04017452,0.05954788,0.01122599,0.8844811,0.0001500706],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01963441,0.00607029,0.4429125,0.0009597626,0.0003141784,0.0008372164,0.2837495,0.2106942,0.03482803],"genre_scores_gemma":[0.08139395,0.008030239,0.3082428,0.001845036,0.0001216706,0.003392256,0.5552135,0.01962578,0.02213477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02756681,"threshold_uncertainty_score":0.09222019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05594504058737552,"score_gpt":0.2584143192889149,"score_spread":0.2024692787015394,"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."}}