{"id":"W3090729831","doi":"10.1109/iscas45731.2020.9181231","title":"Using Machine Learning for Person Identification through Physical Activities","year":2020,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Identification (biology); Computer science; Machine learning; Artificial intelligence; Artificial neural network; Focus (optics); Physical activity; Performing arts; Human–computer interaction","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001173172,0.0001035966,0.0001630466,0.00002742993,0.0001798705,0.0002446847,0.0002572959,0.0000295065,0.00001106084],"category_scores_gemma":[0.00008346184,0.0001007217,0.000098351,0.0001994968,0.00001949284,0.001359918,0.0000694366,0.0001073198,0.00003475638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003786604,"about_ca_system_score_gemma":0.00003032676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009798868,"about_ca_topic_score_gemma":0.000008718101,"domain_scores_codex":[0.9991146,0.00008610708,0.0001201668,0.0003421587,0.0001821177,0.0001548869],"domain_scores_gemma":[0.9994264,0.0002030988,0.0001094486,0.0001488636,0.00006314574,0.00004908095],"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":[0.00006492249,0.0002498409,0.001455428,0.000260067,0.0001546264,0.00000550402,0.05333936,0.0009473288,0.6843072,0.02601033,0.0009450351,0.2322604],"study_design_scores_gemma":[0.000243821,0.00006465318,0.00006873073,0.00001120432,0.00000877718,0.000006062545,0.0007786425,0.9414845,0.0538264,0.0003050256,0.003050555,0.0001515935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07745872,0.00003153388,0.9195942,0.001590681,0.0001392821,0.0002337978,0.00000343148,0.0002872381,0.0006611656],"genre_scores_gemma":[0.9877712,0.000001139442,0.01139685,0.0002877687,0.0002236829,0.00002372565,0.000005369498,0.00001111086,0.0002791367],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9405372,"threshold_uncertainty_score":0.410731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1764975119754803,"score_gpt":0.3299452367145906,"score_spread":0.1534477247391103,"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."}}