{"id":"W3080387846","doi":"10.3390/s20226486","title":"A Benchmark of Data Stream Classification for Human Activity Recognition on Connected Objects","year":2020,"lang":"en","type":"preprint","venue":"Sensors","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Classifier (UML); Power consumption; Artificial intelligence; Machine learning; Benchmark (surveying); Data stream; Data mining; Pattern recognition (psychology); Power (physics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001681111,0.00142777,0.0009022562,0.002153127,0.0004869588,0.001073645,0.001441492,0.001219503,0.001294748],"category_scores_gemma":[0.005829171,0.0001690346,0.0005955475,0.002597824,0.0004594285,0.001178083,0.0005848085,0.0007039892,0.0009750443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008639906,"about_ca_system_score_gemma":0.0008344519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007057698,"about_ca_topic_score_gemma":0.004554241,"domain_scores_codex":[0.9986896,0.0002554839,0.000162336,0.0003697391,0.0004056586,0.0001171793],"domain_scores_gemma":[0.9981964,0.0007484466,0.0001253057,0.0003287506,0.0004669552,0.000134197],"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":[0.002587992,0.001636853,0.0268162,0.0017136,0.0006112774,0.0006889817,0.0002884477,0.2541158,0.01259734,0.003165909,0.03985156,0.655926],"study_design_scores_gemma":[0.0001418566,0.0008365891,0.01573496,0.00006911493,0.00006284302,0.0004014827,0.0002130622,0.9495832,0.01995715,0.004358588,0.008603224,0.00003802139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7885042,0.004613808,0.1568477,0.0010114,0.0009195849,0.0009610648,0.01739296,0.01976003,0.009989141],"genre_scores_gemma":[0.8427881,0.001131684,0.1225581,0.0002143842,0.0001648123,0.0004424144,0.02919039,0.0002944652,0.003215806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007057698,"threshold_uncertainty_score":0.01403326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2656751714502961,"score_gpt":0.3782616634232677,"score_spread":0.1125864919729716,"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."}}