{"id":"W3216654098","doi":"10.18280/ts.380528","title":"Investigating EEG Signals of Autistic Individuals Using Detrended Fluctuation Analysis","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Detrended fluctuation analysis; Electroencephalography; Hurst exponent; Autism spectrum disorder; Psychology; Pattern recognition (psychology); Similarity (geometry); Scalp; Mismatch negativity; Audiology; Autism; Computer science; Artificial intelligence; Developmental psychology; Neuroscience; Mathematics; Statistics; Medicine","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":[0.0002226105,0.0003029006,0.0002437257,0.001136602,0.0001371052,0.0003477631,0.0001044604,0.000196131,0.0007951221],"category_scores_gemma":[0.00183743,0.00005657222,0.0002458638,0.0007221526,0.0001442395,0.0001904958,0.0001748272,0.0001869953,0.0001677699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000859245,"about_ca_system_score_gemma":0.00006724777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001202418,"about_ca_topic_score_gemma":0.001232515,"domain_scores_codex":[0.9998544,0.00003483926,0.00001655507,0.00003704139,0.00004175747,0.00001531892],"domain_scores_gemma":[0.999513,0.0002331033,0.00008436334,0.00004025012,0.0000958454,0.00003346838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001384911,0.0002714102,0.3230098,0.0007151306,0.0005123536,0.005586718,0.004104365,0.007559414,0.3187036,0.00144489,0.002124951,0.3345824],"study_design_scores_gemma":[0.00001426462,0.0004174078,0.9601087,0.00003240912,0.00007915062,0.003632898,0.001052582,0.02160783,0.01030244,0.0009848026,0.001720444,0.00004700081],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804018,0.0003311902,0.0168969,0.0001013547,0.0000237856,0.00005253961,0.0006015765,0.0001149657,0.001475866],"genre_scores_gemma":[0.9883718,0.0002476243,0.01037819,0.0000212129,0.00001672897,0.00003656267,0.0004480957,0.00001573205,0.0004639361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001202418,"threshold_uncertainty_score":0.002659976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05733491236612933,"score_gpt":0.2494785084910527,"score_spread":0.1921435961249233,"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."}}