{"id":"W3155578757","doi":"10.2196/28020","title":"Integrating Behavior of Children with Profound Intellectual, Multiple, or Severe Motor Disabilities With Location and Environment Data Sensors for Independent Communication and Mobility: App Development and Pilot Testing","year":2021,"lang":"en","type":"article","venue":"JMIR Rehabilitation and Assistive Technologies","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Ministry of Internal Affairs and Communications","keywords":"Observational study; Psychology; Categorization; Intellectual disability; Affect (linguistics); Computer science; Developmental psychology; Medicine; Communication; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0007924192,0.0002440494,0.0003720817,0.0001251929,0.0008034476,0.00002254859,0.0002172626,0.0002041887,0.000006456823],"category_scores_gemma":[0.007833265,0.0001734259,0.000009680623,0.0002319917,0.002113031,0.0002320458,0.0009036686,0.0004650464,3.854232e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001437335,"about_ca_system_score_gemma":0.0001964023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007309465,"about_ca_topic_score_gemma":0.0009020976,"domain_scores_codex":[0.9980973,0.0003090819,0.0005728574,0.0006530406,0.0001573268,0.0002103901],"domain_scores_gemma":[0.9909208,0.007287017,0.000378657,0.0009469202,0.0004229264,0.00004361938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004193594,0.0004074672,0.9272158,0.0005923005,0.00006830723,2.027623e-7,0.004183532,0.000001202749,0.000483297,0.0005828206,0.00001699492,0.06602878],"study_design_scores_gemma":[0.001291485,0.001124285,0.8755909,0.0005207939,0.00006174602,0.00001469899,0.1199724,0.0004259793,0.0003282563,0.0002554363,0.0001914348,0.0002226256],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910765,0.0005213694,0.003159554,0.001103919,0.000007173417,0.003717648,0.0001081069,0.0002759768,0.00002970757],"genre_scores_gemma":[0.8478371,0.0001573614,0.149103,0.00001505194,0.000002657133,0.002669034,0.0001245959,0.0000174037,0.00007376474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1459435,"threshold_uncertainty_score":0.9377716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1050083745315817,"score_gpt":0.3755212080603403,"score_spread":0.2705128335287587,"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."}}