{"id":"W2036845658","doi":"10.1109/iembs.2011.6091299","title":"Change-of-state determination to recognize mobility activities using a BlackBerry smartphone","year":2011,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"","keywords":"Accelerometer; Timer; Computer science; Context (archaeology); Global Positioning System; Wearable computer; Elevator; Identification (biology); Real-time computing; Embedded system; Human–computer interaction; Microcontroller; Engineering","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":[0.0001265409,0.0004239122,0.0003054165,0.000426016,0.000157772,0.0002564841,0.0003202946,0.0002941621,0.002596926],"category_scores_gemma":[0.0006115201,0.0001254803,0.0001581746,0.000180084,0.00007859295,0.0002680087,0.0001958909,0.0001505025,0.0007339088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001252453,"about_ca_system_score_gemma":0.0001268271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000936841,"about_ca_topic_score_gemma":0.002676027,"domain_scores_codex":[0.9998757,0.00001423616,0.00000890407,0.00005085509,0.00003664572,0.000013712],"domain_scores_gemma":[0.9997754,0.00007083736,0.00003810442,0.00001722543,0.00007696726,0.0000214608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008876232,0.0002887257,0.01645018,0.0003388375,0.00008310646,0.0004561093,0.0003716302,0.002690479,0.5282881,0.000431115,0.002908034,0.446806],"study_design_scores_gemma":[0.0002063851,0.003012032,0.189542,0.0001352503,0.0002412346,0.002591156,0.0004899299,0.3265671,0.458784,0.001070506,0.01721616,0.000144242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7087364,0.0003467153,0.2810709,0.0001663718,0.0001187296,0.0004560316,0.0006926946,0.004549901,0.003862184],"genre_scores_gemma":[0.8875493,0.0001454314,0.1087987,0.00007113942,0.00002807616,0.0002206292,0.0002441688,0.00004931059,0.002893174],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002596926,"threshold_uncertainty_score":0.008687556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1757451276941099,"score_gpt":0.2980822269059269,"score_spread":0.122337099211817,"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."}}