{"id":"W4394951289","doi":"10.1109/jsen.2024.3388893","title":"Centaur: Robust Multimodal Fusion for Human Activity Recognition","year":2024,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fusion; Sensor fusion; Activity recognition; Computer science; Centaur; Artificial intelligence; Computer vision; Pattern recognition (psychology); 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":[0.001039475,0.001184478,0.00100939,0.000945401,0.000276026,0.0006061586,0.001043881,0.0009756014,0.002717264],"category_scores_gemma":[0.002574617,0.0003225847,0.0009476714,0.0006198133,0.0004357196,0.001073486,0.001864559,0.001245147,0.001590004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005057361,"about_ca_system_score_gemma":0.0005787031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0036215,"about_ca_topic_score_gemma":0.004550449,"domain_scores_codex":[0.9994937,0.0001046721,0.00002007649,0.0001963357,0.0001153425,0.00006989497],"domain_scores_gemma":[0.99967,0.00009775113,0.00003695757,0.00006543053,0.00009400329,0.0000358108],"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":[0.000870324,0.0004148169,0.006598282,0.0002730135,0.0004304093,0.0001988716,0.000211418,0.1272205,0.04196399,0.002471123,0.02046442,0.7988828],"study_design_scores_gemma":[0.0000306958,0.0002923409,0.008007028,0.00004155939,0.00008306208,0.0003026968,0.00005867916,0.9555959,0.0246502,0.005500023,0.005371829,0.00006592394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05833258,0.001665612,0.9195784,0.0003640507,0.0003370218,0.00016299,0.001875964,0.01455982,0.003123507],"genre_scores_gemma":[0.7385237,0.0007459703,0.2473794,0.0006317454,0.0002105811,0.0003429179,0.005460636,0.0004698339,0.00623522],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0036215,"threshold_uncertainty_score":0.009090126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07571047175349337,"score_gpt":0.3072349701069163,"score_spread":0.2315244983534229,"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."}}