{"id":"W4224252851","doi":"10.2196/35406","title":"Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study","year":2022,"lang":"en","type":"article","venue":"JMIR Pediatrics and Parenting","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; U.S. National Library of Medicine; Weston Havens Foundation; Bill and Melinda Gates Foundation; Wu Tsai Neurosciences Institute, Stanford University; National Science Foundation; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Hartwell Foundation","keywords":"Neurotypical; Autism; Autism spectrum disorder; Computer science; Speech recognition; Convolutional neural network; Spectrogram; Mel-frequency cepstrum; Random forest; Artificial intelligence; Feature extraction; Psychology; Developmental psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0005107586,0.0002667706,0.0003529884,0.0002609279,0.001955557,0.0003248789,0.0004807356,0.00006244763,0.0003332975],"category_scores_gemma":[0.0002652011,0.0002924819,0.00007737789,0.0008009169,0.00004384041,0.0001462479,0.0009522887,0.001481219,0.000007961949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000101195,"about_ca_system_score_gemma":0.00006773789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004812016,"about_ca_topic_score_gemma":0.00004599892,"domain_scores_codex":[0.9966664,0.0004072723,0.0004894985,0.0008934512,0.0009139456,0.0006294642],"domain_scores_gemma":[0.9988123,0.0003860806,0.0003468874,0.0002879393,0.000009723845,0.0001570632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000903822,0.0004078438,0.9498296,0.00005445255,0.00001376905,0.00009054833,0.008460325,0.01799495,0.0150696,0.0003868397,0.0001983002,0.007403401],"study_design_scores_gemma":[0.001399572,0.0002508281,0.03393785,0.000006715476,0.00004812769,0.00001909085,0.002426056,0.9567957,0.0005651054,0.002792813,0.001186159,0.0005720075],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967784,0.0003408118,0.0005058378,0.0003488572,0.0002127971,0.0006035648,0.00007080593,0.0002114451,0.0009274943],"genre_scores_gemma":[0.9986438,0.00004113392,0.0003205167,0.00005781956,0.0001099657,0.0001042991,0.0000341496,0.00005923851,0.0006290839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9388007,"threshold_uncertainty_score":0.9999527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05061827685488698,"score_gpt":0.3198674960015697,"score_spread":0.2692492191466827,"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."}}