{"id":"W1527867680","doi":"10.1007/11556114_28","title":"2D-3D MultiAgent GeoSimulation with Knowledge-Based Agents of Customers’ Shopping Behavior in a Shopping Mall","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Shopping mall; Situational ethics; Computer science; Human–computer interaction; Advertising; Business; Psychology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005147427,0.0005426439,0.0006231383,0.0019361,0.000175335,0.0002165347,0.0007431481,0.0001982894,0.00008315268],"category_scores_gemma":[0.00004656202,0.0005007657,0.0001177427,0.0007898518,0.0004860454,0.0007202562,0.0006081087,0.0005045921,0.0000347136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003482745,"about_ca_system_score_gemma":0.0001708163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001531633,"about_ca_topic_score_gemma":0.003409562,"domain_scores_codex":[0.9971196,0.00001147301,0.0006380549,0.0009749828,0.0007105116,0.0005453528],"domain_scores_gemma":[0.9984362,0.0001532945,0.0004807374,0.0005412152,0.0003623365,0.00002626028],"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":[0.0000385985,0.0001597648,0.2592983,0.0002589466,0.00001726105,0.0000813194,0.0002042695,0.05353613,0.000171173,0.0001511599,0.000002104026,0.686081],"study_design_scores_gemma":[0.002262517,0.00007630816,0.1996348,0.003538819,0.0003293826,0.000007461687,0.000004004095,0.7871436,0.00008094625,0.00005821623,0.005168838,0.001695158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5084901,0.001914087,0.4748556,0.0006014652,0.002244735,0.004048764,0.00001348891,0.0003432317,0.007488478],"genre_scores_gemma":[0.9894869,0.000009100881,0.009746987,0.0003035727,0.0002365806,0.00003626949,0.00001621262,0.00005758365,0.0001067635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7336075,"threshold_uncertainty_score":0.9997444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03996756806424145,"score_gpt":0.2726812916668973,"score_spread":0.2327137236026558,"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."}}