{"id":"W3161600009","doi":"10.2196/29242","title":"Informing Developmental Milestone Achievement for Children With Autism: Machine Learning Approach","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Milestone; Machine learning; Autism spectrum disorder; Autism; Developmental Milestone; Artificial intelligence; Computer science; Psychology; Developmental psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00260248,0.0006704211,0.0006560236,0.003386927,0.0004159301,0.001210836,0.001074068,0.0007844652,0.001309354],"category_scores_gemma":[0.01199692,0.000243151,0.0006064131,0.001945625,0.0003848383,0.001068628,0.0007630439,0.001294188,0.0002865586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001524603,"about_ca_system_score_gemma":0.001487604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01090431,"about_ca_topic_score_gemma":0.01376824,"domain_scores_codex":[0.9985406,0.0008780417,0.00008912697,0.0002717285,0.0001362336,0.00008421554],"domain_scores_gemma":[0.9899939,0.008017256,0.0008086549,0.0002971379,0.0006860753,0.000197084],"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":[0.0002020093,0.001214908,0.4552959,0.0004282541,0.000448989,0.0002746448,0.001185709,0.2198344,0.0007642264,0.00508035,0.003778302,0.3114923],"study_design_scores_gemma":[0.00001901672,0.0002919205,0.06250425,0.0001767582,0.00008534674,0.0001084355,0.001091556,0.9224946,0.0008671627,0.01057942,0.001742202,0.0000393213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6371868,0.001844214,0.3413256,0.00515919,0.00008154561,0.0006497134,0.002933329,0.0007973607,0.01002231],"genre_scores_gemma":[0.9195637,0.0003945148,0.07814743,0.0001399516,0.00003437738,0.0002483132,0.000778982,0.00001350689,0.0006790903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01090431,"threshold_uncertainty_score":0.02168167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0326435305297664,"score_gpt":0.3777100651790863,"score_spread":0.3450665346493199,"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."}}