{"id":"W2772057147","doi":"10.1016/j.jaac.2017.10.019","title":"Effects of State Autism Mandate Age Caps on Health Service Use and Spending Among Adolescents","year":2017,"lang":"en","type":"article","venue":"Journal of the American Academy of Child & Adolescent Psychiatry","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Health Economics","funders":"National Institute of Mental Health","keywords":"Mandate; Autism; Demography; Autism spectrum disorder; Medicine; Young adult; Medicaid; Health care; Gerontology; Psychology; Psychiatry; Economics; Political science","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":[0.001682216,0.0002096039,0.0003901404,0.0007383937,0.0007218334,0.001591358,0.0008160383,0.001306133,0.004997431],"category_scores_gemma":[0.009212111,0.0003884281,0.001124774,0.0006534698,0.0006383987,0.0008115774,0.002189558,0.001572452,0.0004045364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003432712,"about_ca_system_score_gemma":0.003526245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1761459,"about_ca_topic_score_gemma":0.2563176,"domain_scores_codex":[0.9977139,0.0006768013,0.0001239295,0.0001726066,0.0002645435,0.001048193],"domain_scores_gemma":[0.9891835,0.003067179,0.003989902,0.0003533323,0.0008974854,0.002508467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000768574,0.0006102666,0.9851348,0.00002231013,0.0001689518,0.0001446206,0.0002960867,0.002252067,0.0001808049,0.001756992,0.003993966,0.004670651],"study_design_scores_gemma":[0.00002846042,0.0001427479,0.9962258,0.00001973442,0.00007485553,0.0000422662,0.0008019243,0.001180093,0.0002177998,0.0001870872,0.001070691,0.000008346761],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942263,0.0001836684,0.00005037527,0.001622525,0.00003821338,0.00001160043,0.00171712,0.00001237741,0.002137894],"genre_scores_gemma":[0.9973164,0.00008258554,0.00004251496,0.0002799887,0.0000258726,0.0000215277,0.001041836,0.000003570532,0.001185601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1761459,"threshold_uncertainty_score":0.3502412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0285004189004301,"score_gpt":0.2934773070430787,"score_spread":0.2649768881426486,"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."}}