{"id":"W3048354284","doi":"10.1111/epi.16633","title":"Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy","year":2020,"lang":"en","type":"article","venue":"Epilepsia","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"Medical Research Council; Alan Turing Institute","keywords":"Epilepsy; Big data; Data science; Computer science; Medicine; Psychiatry; Data mining","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":[0.03731919,0.001411398,0.001564646,0.005259919,0.00177126,0.008309682,0.001994407,0.007192272,0.005212937],"category_scores_gemma":[0.0571841,0.0008727313,0.001693053,0.006984448,0.003475407,0.01323136,0.006352545,0.01110932,0.002536567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004383306,"about_ca_system_score_gemma":0.01820532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01209123,"about_ca_topic_score_gemma":0.02158308,"domain_scores_codex":[0.9897764,0.002946949,0.001827847,0.0007591215,0.003815509,0.0008742899],"domain_scores_gemma":[0.9204143,0.04315624,0.005762897,0.002613262,0.01984064,0.008212544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001113641,0.00003259797,0.001651175,0.002069167,0.00009420292,0.0002016268,0.00023988,0.0002438768,0.0001934298,0.01368161,0.8202059,0.1612753],"study_design_scores_gemma":[0.00004318493,0.00005138609,0.00408808,0.01136718,0.0001002746,0.0004746256,0.0004163525,0.0003404681,0.0001638514,0.01641195,0.9664673,0.00007537549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.000392456,0.2601986,0.001452701,0.7182151,0.01321071,0.000092793,0.001641405,0.00009735906,0.004698867],"genre_scores_gemma":[0.009923584,0.6873375,0.007151634,0.2439744,0.04241144,0.0003965999,0.00403295,0.0001892713,0.004582704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03731919,"threshold_uncertainty_score":0.1973652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.183560606791995,"score_gpt":0.3708631319615985,"score_spread":0.1873025251696036,"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."}}