{"id":"W3046740011","doi":"10.3390/brainsci10080504","title":"Distinguishing and Biochemical Phenotype Analysis of Epilepsy Patients Using a Novel Serum Profiling Platform","year":2020,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Fogarty International Center; Volvo Research and Educational Foundations; U.S. Department of Defense","keywords":"Profiling (computer programming); Epilepsy; Phenotype; Computational biology; Medicine; Bioinformatics; Neuroscience; Psychology; Biology; Computer science; Genetics; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005623375,0.000423516,0.0003902378,0.001064532,0.0001935248,0.0006278214,0.0001650711,0.0003711324,0.0008748806],"category_scores_gemma":[0.001049637,0.0001232718,0.0002895681,0.0005432182,0.000158531,0.0002301308,0.0003836831,0.0003487808,0.0003095466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001632919,"about_ca_system_score_gemma":0.0001928392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000400023,"about_ca_topic_score_gemma":0.0005527257,"domain_scores_codex":[0.9996505,0.00006377257,0.00004383505,0.0001022943,0.00009441312,0.0000452651],"domain_scores_gemma":[0.9996293,0.00008447387,0.0001068205,0.000032743,0.0001026279,0.00004419022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002300393,0.0005297812,0.5568905,0.0002435006,0.0002767259,0.001223167,0.0004202417,0.0009334631,0.3616192,0.000285675,0.0009452811,0.07433209],"study_design_scores_gemma":[0.0001009866,0.003348882,0.8524299,0.00006298444,0.0002904064,0.00791766,0.0004097854,0.01472749,0.1161743,0.0006712154,0.003799492,0.00006691417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930418,0.0004880152,0.004420698,0.0001081906,0.00002864163,0.00006849657,0.0008692195,0.0001197844,0.0008552308],"genre_scores_gemma":[0.9913305,0.0002394266,0.006554159,0.0001201846,0.00002246514,0.00006701704,0.001085802,0.00001252169,0.0005679592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001064532,"threshold_uncertainty_score":0.002973974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09482658644553073,"score_gpt":0.3516585427987497,"score_spread":0.256831956353219,"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."}}