{"id":"W4392450436","doi":"10.1007/s00521-024-09458-8","title":"Assessment of machine learning strategies for simplified detection of autism spectrum disorder based on the gut microbiome composition","year":2024,"lang":"en","type":"article","venue":"Neural Computing and Applications","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Instituto Tecnológico y de Estudios Superiores de Monterrey","keywords":"Computational Science and Engineering; Autism spectrum disorder; Microbiome; Gut microbiome; Computer science; Composition (language); Artificial intelligence; Autism; Machine learning; Computational biology; Biology; Psychology; Bioinformatics; Developmental psychology","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":[0.005052651,0.0009441116,0.0007731048,0.001635293,0.0003585358,0.001442789,0.0007194298,0.00103379,0.001115245],"category_scores_gemma":[0.01457089,0.0002000535,0.0005544833,0.0005583846,0.0002803473,0.0008113779,0.0008451137,0.0007642079,0.0004734847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005986893,"about_ca_system_score_gemma":0.001204085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002933208,"about_ca_topic_score_gemma":0.002918864,"domain_scores_codex":[0.9989086,0.00054403,0.00007605595,0.0002060477,0.0001818446,0.00008335692],"domain_scores_gemma":[0.9920032,0.006313998,0.0003668104,0.000296219,0.0008089072,0.0002108559],"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":[0.003492005,0.000809786,0.136654,0.000603201,0.00110632,0.0002105622,0.0001831662,0.2023662,0.03070255,0.003633002,0.002882299,0.617357],"study_design_scores_gemma":[0.00006260084,0.0004827913,0.0209616,0.00004556515,0.00014498,0.000146666,0.00008069567,0.9673634,0.007850435,0.002376352,0.000454692,0.00003022621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7294972,0.003566274,0.2585303,0.001196398,0.0001247077,0.0002507851,0.001034233,0.001774383,0.004025762],"genre_scores_gemma":[0.9192747,0.0004288411,0.07867226,0.0001327147,0.00003873316,0.0001001183,0.0007229503,0.00004612151,0.0005835927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005052651,"threshold_uncertainty_score":0.0267213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009902915437581011,"score_gpt":0.2973083063304962,"score_spread":0.2874053908929152,"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."}}