{"id":"W1497626821","doi":"10.3233/tad-130369","title":"Understanding the Nintendo Wii and Microsoft Kinect consoles in long-term care facilities","year":2013,"lang":"en","type":"article","venue":"Technology and Disability","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Term (time); Computer science; Computer graphics (images); Simulation; Physical medicine and rehabilitation; Medicine; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002577011,0.0001299685,0.0001929743,0.0001046631,0.000517805,0.00004891858,0.0002612587,0.0003712692,0.00007030959],"category_scores_gemma":[0.000577482,0.00009866522,0.00002384873,0.0003306121,0.01040293,0.0001590688,0.0001909571,0.0003395397,0.000008081254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001620076,"about_ca_system_score_gemma":0.00003514389,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001880623,"about_ca_topic_score_gemma":0.02937625,"domain_scores_codex":[0.9989491,0.00009848052,0.0001776387,0.0003415329,0.00007982581,0.0003534131],"domain_scores_gemma":[0.9992967,0.000276481,0.00004225639,0.0003027499,0.00004085234,0.00004094546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005674361,0.00002293721,0.9348096,0.0000376901,0.000006889839,0.000001584586,0.008683463,6.886876e-8,0.00009845635,0.05037905,0.00003419584,0.0059204],"study_design_scores_gemma":[0.0004092709,0.0000533782,0.6670812,0.00003947875,0.000009501307,0.000009564968,0.1974937,0.000002776844,0.000267818,0.1342711,0.0001958941,0.0001663005],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828541,0.001428764,0.0001027395,0.01367043,0.00005363143,0.0005455894,0.00001138763,0.0003725566,0.0009608483],"genre_scores_gemma":[0.999622,0.0001143696,0.00004730901,0.00004329495,0.000009139469,0.00006978503,0.000001649001,0.000004980685,0.00008750052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2677284,"threshold_uncertainty_score":0.9922902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03294404827669478,"score_gpt":0.2849125095245854,"score_spread":0.2519684612478906,"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."}}