{"id":"W4316467216","doi":"10.18280/ts.390619","title":"Wavelet Scattering Transform and Deep Learning Networks based Autism Spectrum Disorder Identification using EEG Signals","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Abdulaziz University; Simons Foundation Autism Research Initiative","keywords":"Electroencephalography; Autism spectrum disorder; Artificial intelligence; Autism; Pattern recognition (psychology); Wavelet; Psychology; Computer science; Identification (biology); Speech recognition; Audiology; Developmental psychology; Neuroscience; Medicine; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003157892,0.0005805939,0.000238191,0.0006778696,0.0001442883,0.0003386479,0.0002852426,0.0003420196,0.0009369146],"category_scores_gemma":[0.0007320361,0.0001245587,0.0004133675,0.000300887,0.0001767994,0.0003312385,0.000424087,0.000410923,0.0002528577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003448535,"about_ca_system_score_gemma":0.0003090182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004220855,"about_ca_topic_score_gemma":0.00442697,"domain_scores_codex":[0.9998858,0.00002155842,0.000008446287,0.0000327734,0.00002917828,0.00002224885],"domain_scores_gemma":[0.9998729,0.00005267442,0.00001964331,0.000008020358,0.00003542833,0.00001131483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009765729,0.0006684744,0.02477796,0.0001881188,0.0002232178,0.0006816609,0.0002281693,0.2672958,0.07564396,0.002688119,0.002984473,0.6236436],"study_design_scores_gemma":[0.000007392866,0.0001044069,0.006269104,0.00001013343,0.0000184211,0.00007484511,0.00003858406,0.9851087,0.007237114,0.0007334181,0.0003905055,0.000007308186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6498567,0.000967444,0.3427706,0.00044377,0.0001198521,0.0001197555,0.000557984,0.001008173,0.004155732],"genre_scores_gemma":[0.9420604,0.0003612636,0.05361601,0.00006997299,0.00003450844,0.00007376214,0.0007586224,0.00002462719,0.003000855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004220855,"threshold_uncertainty_score":0.008392572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02461438632947962,"score_gpt":0.2681672065915641,"score_spread":0.2435528202620845,"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."}}