{"id":"W2972599533","doi":"10.18687/laccei2019.1.1.278","title":"A technological platform using serious game for children with Autism Spectrum Disorder (ASD) in Peru","year":2019,"lang":"en","type":"article","venue":"Proceedings of the 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Industry, Innovation, and Infrastructure for Sustainable Cities and Communities”","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Autism spectrum disorder; Serious game; Autism; Computer science; Psychology; Developmental psychology; Multimedia","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":[0.0006986973,0.0006374533,0.0004865807,0.0005961438,0.001051233,0.0006910066,0.0006307905,0.0004488497,0.002549818],"category_scores_gemma":[0.002275291,0.0002685286,0.0006916951,0.0002150782,0.0005743428,0.0006310242,0.001566208,0.0007279303,0.0006846893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005312248,"about_ca_system_score_gemma":0.001005742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005120289,"about_ca_topic_score_gemma":0.01421709,"domain_scores_codex":[0.9996839,0.00008600315,0.00002628725,0.0000587324,0.00005518788,0.00008985718],"domain_scores_gemma":[0.9993173,0.0001588141,0.00006818872,0.00005183731,0.0001044637,0.0002994704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002764475,0.05424168,0.3708574,0.001186635,0.0001703259,0.02016649,0.1108182,0.001353539,0.07632326,0.001416599,0.006812064,0.3538894],"study_design_scores_gemma":[0.0008682868,0.03633215,0.8086045,0.000357559,0.000371841,0.008174122,0.09636992,0.007426146,0.01563342,0.00222192,0.02341729,0.0002228151],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985399,0.00002106638,0.0003143233,0.00007407358,0.00000572019,0.0001021609,0.00003969947,0.00004695834,0.0008560783],"genre_scores_gemma":[0.9920564,0.0001309543,0.004709414,0.00005316235,0.000003455069,0.0005313045,0.0001377651,0.00001349369,0.002363916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005120289,"threshold_uncertainty_score":0.01018095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280993256626448,"score_gpt":0.2596270491836929,"score_spread":0.2468171166174285,"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."}}