{"id":"W2316255109","doi":"10.1541/ieejias.134.332","title":"Infant Monitoring System using Activity Recognition","year":2014,"lang":"en","type":"article","venue":"IEEJ Transactions on Industry Applications","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alpha Technologies (Canada)","funders":"","keywords":"Activity recognition; Feature (linguistics); Computer science; Medical care; Acceleration; Physical activity; Physical medicine and rehabilitation; Artificial intelligence; Medical emergency; Pattern recognition (psychology); Medicine; Family 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":[0.0004204688,0.0007756242,0.0009382148,0.001118457,0.0002242968,0.0005750456,0.0009656022,0.000546321,0.004842256],"category_scores_gemma":[0.000831781,0.0002203757,0.0002921133,0.0005571109,0.00008217657,0.0005815912,0.0005197501,0.0003503791,0.002820765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002668631,"about_ca_system_score_gemma":0.0002915979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001816173,"about_ca_topic_score_gemma":0.001256465,"domain_scores_codex":[0.9994529,0.00006323615,0.00006639567,0.0002122328,0.0001604241,0.00004491176],"domain_scores_gemma":[0.9994441,0.00007105729,0.00007448524,0.00006898218,0.0002791621,0.00006231807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001220249,0.0005003135,0.02258238,0.0004285704,0.0001565737,0.0009111482,0.0001855727,0.004276702,0.1485979,0.0009177245,0.0202153,0.8000076],"study_design_scores_gemma":[0.0003126696,0.002292305,0.1122469,0.0001870959,0.0005391295,0.004108319,0.0002339166,0.5561026,0.2585132,0.001819403,0.06333574,0.0003087719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2248665,0.002843109,0.664143,0.0004529266,0.0005619748,0.0008751901,0.005588883,0.08126996,0.01939844],"genre_scores_gemma":[0.8528357,0.0007966404,0.1274674,0.0004527879,0.0001744378,0.0006517273,0.003787031,0.0003093935,0.01352487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004842256,"threshold_uncertainty_score":0.01619893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05676798527803154,"score_gpt":0.2830244315105732,"score_spread":0.2262564462325416,"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."}}