{"id":"W2127666915","doi":"10.1155/s1110865704402212","title":"Generic Multimedia Multimodal Agents Paradigms and Their Dynamic Reconfiguration at the Architectural Level","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control reconfiguration; Computer science; Adaptation (eye); Architecture; Dialog box; Distributed computing; Intelligent agent; Human–computer interaction; Computer architecture; Multimedia; Artificial intelligence; Embedded system; World Wide Web","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":[0.0007430543,0.0005086299,0.0002553645,0.0004055572,0.0004983855,0.001287994,0.001014504,0.001021006,0.001331781],"category_scores_gemma":[0.0009479166,0.0002596653,0.0005893653,0.0003177274,0.001134169,0.001895344,0.001160126,0.0008721444,0.0004152989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007071037,"about_ca_system_score_gemma":0.000476078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009830527,"about_ca_topic_score_gemma":0.001475203,"domain_scores_codex":[0.9995542,0.0001511739,0.00004071092,0.00009128894,0.0001073499,0.00005518367],"domain_scores_gemma":[0.9996165,0.00006304766,0.00005823169,0.0001415406,0.00008059051,0.00004004687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001683402,0.00008515565,0.001688223,0.0003142973,0.00009874309,0.000731196,0.001491544,0.1252242,0.06847262,0.6713964,0.002880194,0.1274491],"study_design_scores_gemma":[0.00004353069,0.0001869973,0.001440671,0.00008612964,0.0001179797,0.000766568,0.0004848118,0.6483563,0.03480744,0.2403123,0.07332885,0.00006838314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04996618,0.0007359794,0.9341487,0.0003047469,0.00004796338,0.0001319272,0.00005569551,0.0007445654,0.01386421],"genre_scores_gemma":[0.5034579,0.0009413,0.4863646,0.0001811001,0.00004337094,0.0003806625,0.00019266,0.00009971726,0.008338676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001331781,"threshold_uncertainty_score":0.00513041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0283473141563663,"score_gpt":0.2815415284132414,"score_spread":0.253194214256875,"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."}}