{"id":"W2548477800","doi":"10.1109/tic-sth.2009.5444501","title":"A time-dependent agent-based model of an eco-product market with social interactions and dynamic game pricing schemes","year":2009,"lang":"en","type":"article","venue":"","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dynamic pricing; Computer science; Product (mathematics); Sequential game; Game theory; Microeconomics; Multi-agent system; Agent-based model; Economics; Artificial intelligence; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001013303,0.0001121257,0.0001959532,0.000333275,0.0001612493,0.00011817,0.000188831,0.00002976106,0.0009767186],"category_scores_gemma":[0.0002883936,0.00007676754,0.00003653931,0.0005176214,0.0000771203,0.0003672874,0.00003490622,0.0001088172,0.00001623586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002869796,"about_ca_system_score_gemma":0.00007398963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000653413,"about_ca_topic_score_gemma":0.00005139624,"domain_scores_codex":[0.9983583,0.00006001725,0.0004444679,0.0003485263,0.0006324699,0.0001561838],"domain_scores_gemma":[0.9989871,0.0001107272,0.0002539999,0.0002298201,0.0003664159,0.00005197883],"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":[0.001069842,0.001211931,0.002003068,0.00002371591,0.00005648426,0.00001303065,0.004465538,0.02101402,0.1668042,0.004124389,0.005487,0.7937268],"study_design_scores_gemma":[0.0004562054,0.00008418232,0.003076835,0.00001208445,0.00000708547,0.000006918195,0.0005882985,0.992529,0.001860736,0.001128062,0.0001357301,0.0001148596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9309813,0.000003730501,0.05346212,0.0009909457,0.00003780381,0.0001296698,0.000007539332,0.00004750329,0.01433944],"genre_scores_gemma":[0.9818429,3.496781e-7,0.009430353,0.0004388916,0.00002016615,0.000002087061,0.000004269205,0.000006854984,0.00825415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.971515,"threshold_uncertainty_score":0.9999365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0617019752221831,"score_gpt":0.3521328087847042,"score_spread":0.290430833562521,"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."}}