{"id":"W2116515896","doi":"10.1109/icc.2002.997291","title":"VELVET: an adaptive hybrid architecture for very large virtual environments","year":2003,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ministério da Educação; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Velvet; Architecture; Computer science; Materials science","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":[0.0003549322,0.0001717347,0.0001872974,0.00008834629,0.0001442431,0.0001011644,0.0004267898,0.00005000198,0.00007754558],"category_scores_gemma":[0.00005011777,0.0001598365,0.00009641183,0.00009961384,0.00002616284,0.000621061,0.00008811098,0.0001138032,0.0001609049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005731797,"about_ca_system_score_gemma":0.00005297338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001025515,"about_ca_topic_score_gemma":0.0000371442,"domain_scores_codex":[0.9985263,0.0001704427,0.0001872228,0.0005079141,0.0002539058,0.0003542088],"domain_scores_gemma":[0.9990501,0.0001993687,0.00007690953,0.000503931,0.00002592843,0.0001437363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000218516,0.002206279,0.0009966154,0.00003172562,0.0003600323,0.00007918442,0.004266463,0.0003227267,0.01459405,0.2817581,0.008885255,0.6862811],"study_design_scores_gemma":[0.004914396,0.00270314,0.001534243,0.00004905759,0.00003099793,0.0002967562,0.0008375696,0.02787093,0.07573482,0.01329582,0.8712595,0.001472743],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02537049,0.00002359034,0.9706263,0.00009606603,0.0003980577,0.0004316261,0.00004240299,0.0001181789,0.002893303],"genre_scores_gemma":[0.9840348,0.000001204216,0.01304074,0.0006354898,0.00006708731,0.00008506068,0.000009459515,0.0000159976,0.002110137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9586644,"threshold_uncertainty_score":0.6517941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02471582807585236,"score_gpt":0.2414366543591449,"score_spread":0.2167208262832926,"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."}}