{"id":"W3081102043","doi":"10.1101/2020.08.23.263236","title":"Modeling Genetic Epileptic Encephalopathies using Brain Organoids","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetics and Neurodevelopmental Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"WWOX; Biology; Neuroscience; Population; Organoid; Phenotype; Epilepsy; Wnt signaling pathway; Medicine; Genetics; Cancer; Signal transduction; Suppressor; 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":[0.0002161284,0.0004987277,0.0002802628,0.0003360962,0.0002599638,0.0005472158,0.0005011442,0.0005045725,0.001098828],"category_scores_gemma":[0.0001353247,0.0002259084,0.0004110866,0.0001568507,0.0005490245,0.0002995458,0.0007961633,0.0007081726,0.000375379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004495804,"about_ca_system_score_gemma":0.0003494562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001373,"about_ca_topic_score_gemma":0.0009319693,"domain_scores_codex":[0.9999123,0.00001628052,0.000006972291,0.00002299142,0.00002954751,0.00001199723],"domain_scores_gemma":[0.9998813,0.00003598106,0.00002329479,0.00002378747,0.00001092482,0.00002477855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008845286,0.0000472413,0.0007059135,0.0001749594,0.00003930934,0.0005511651,0.0001415464,0.06671394,0.9200521,0.006458673,0.0004574682,0.004569345],"study_design_scores_gemma":[0.00004053126,0.0001984726,0.0007733521,0.00004338453,0.00006401871,0.000712105,0.0001263589,0.09961849,0.8684363,0.003139512,0.02681218,0.00003526939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6531987,0.001922104,0.3291554,0.0004615536,0.0003702758,0.0002619273,0.001984066,0.001609031,0.01103704],"genre_scores_gemma":[0.9031956,0.001820695,0.08719732,0.00008347443,0.00001693461,0.0003290901,0.001001266,0.000172654,0.006183049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001373,"threshold_uncertainty_score":0.003675997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01690384358969775,"score_gpt":0.2203102784342061,"score_spread":0.2034064348445084,"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."}}