{"id":"W2293306693","doi":"10.5555/1999416.1999477","title":"DEVS-based modeling of a human motion data synthesis and control system","year":2010,"lang":"en","type":"article","venue":"Summer Computer Simulation Conference","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Animation; DEVS; Motion capture; Motion (physics); Human motion; Computer animation; Artificial intelligence; Motion control; Data modeling; Event (particle physics); Computer vision; Control engineering; Simulation; Modeling and simulation; Robot; Computer graphics (images); Engineering; Database","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":[0.0001669634,0.0001008149,0.0001497568,0.00009444764,0.00006001623,0.00005727974,0.000145947,0.00006305869,0.00003465518],"category_scores_gemma":[0.00001452585,0.0001060706,0.00001828641,0.00005244361,0.00002070942,0.0002200428,0.00002414549,0.0000983272,0.000006405467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009931228,"about_ca_system_score_gemma":0.00001110733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001264261,"about_ca_topic_score_gemma":0.00002710205,"domain_scores_codex":[0.999337,0.00003051986,0.000256409,0.0001698022,0.0001156086,0.00009071489],"domain_scores_gemma":[0.9993959,0.00008469963,0.00005007324,0.0003038582,0.0001213033,0.00004417718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003093687,0.00001122067,0.0007331708,0.0001503426,0.00001343903,3.000797e-7,0.00007392687,0.978185,0.004750192,0.002852946,0.000005056521,0.0132213],"study_design_scores_gemma":[0.0003286771,0.000008865296,0.001603012,0.00007131029,0.00001759586,3.776692e-7,0.00001061993,0.9973711,0.0004295048,0.00003452949,0.00002483807,0.00009958659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2602463,0.000005439843,0.7392099,0.00001109627,0.0001241225,0.00009689036,0.00001817981,0.0001371741,0.0001509638],"genre_scores_gemma":[0.996135,4.133605e-7,0.003706358,0.00001315611,0.000080051,0.000004176904,0.0000466624,0.00001241662,0.0000017406],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7358888,"threshold_uncertainty_score":0.4325432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06884787119788198,"score_gpt":0.2743558368746605,"score_spread":0.2055079656767785,"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."}}