{"id":"W2091566335","doi":"10.1258/1357633054068946","title":"An intelligent emergency response system: preliminary development and testing of automated fall detection","year":2005,"lang":"en","type":"article","venue":"Journal of Telemedicine and Telecare","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":235,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Emergency response; Computer science; Medical emergency; Medicine","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":[0.002595213,0.0006252972,0.000654979,0.0003512235,0.0002743647,0.0004175921,0.001198491,0.0008511949,0.001542121],"category_scores_gemma":[0.005788281,0.0002996046,0.0002320295,0.0002096233,0.0004130065,0.0009442992,0.0004237337,0.0003558704,0.0005929908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001884157,"about_ca_system_score_gemma":0.0005507024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001429905,"about_ca_topic_score_gemma":0.001158564,"domain_scores_codex":[0.998794,0.0004627938,0.0001200486,0.0001905109,0.000341166,0.00009158632],"domain_scores_gemma":[0.9976869,0.0009471652,0.00006927772,0.0001889343,0.0009201635,0.0001875729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004980673,0.009757276,0.05693075,0.002087425,0.0003641133,0.001312868,0.002815718,0.02044512,0.3411377,0.001110997,0.003647129,0.5554103],"study_design_scores_gemma":[0.003319316,0.112226,0.1823782,0.0002993941,0.000844027,0.003771847,0.001418913,0.2801951,0.389884,0.0008604696,0.02451567,0.0002869914],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8963499,0.0002873905,0.09824309,0.0002219172,0.00008342254,0.001413534,0.000230251,0.001649065,0.001521341],"genre_scores_gemma":[0.7936974,0.0003771633,0.2009257,0.0002748361,0.00005875021,0.0009332901,0.0009539066,0.00009700353,0.002681935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002595213,"threshold_uncertainty_score":0.01372498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01674263717618528,"score_gpt":0.2763231407350947,"score_spread":0.2595805035589094,"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."}}