{"id":"W4412368978","doi":"10.1007/s10458-025-09714-8","title":"Diversity-seeking jump games in networks","year":2025,"lang":"en","type":"article","venue":"Autonomous Agents and Multi-Agent Systems","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Price of anarchy; Jump; Mathematical economics; Node (physics); Fraction (chemistry); Diversity (politics); Class (philosophy); Computer science; Function (biology); Stability (learning theory); Mathematical optimization; Mathematics; Economics; Price of stability; Artificial intelligence","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":[0.001783755,0.0001659656,0.0003361162,0.0003102276,0.0007214989,0.0002266632,0.0005552181,0.0001024275,0.00005800734],"category_scores_gemma":[0.000140274,0.0001342305,0.00007785756,0.00056351,0.00008657634,0.0001635009,0.0008347104,0.0001453092,0.00009120572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007434049,"about_ca_system_score_gemma":0.00003236773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005183255,"about_ca_topic_score_gemma":0.0001001158,"domain_scores_codex":[0.9980151,0.0002390551,0.0005981201,0.0005432017,0.0002970545,0.0003074883],"domain_scores_gemma":[0.998779,0.0003742404,0.0001831527,0.0004843601,0.00007537062,0.000103872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004432764,0.0005710177,0.837191,0.00006482792,0.0001425524,0.00005527405,0.008407103,0.03550508,0.0003156792,0.04305447,0.01072239,0.06392626],"study_design_scores_gemma":[0.001322679,0.00002416766,0.4787438,0.0001469391,0.00003718134,0.000006811028,0.003898111,0.3802756,0.00002464279,0.001435888,0.1337475,0.0003366795],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8917679,0.001197433,0.09986929,0.0003483176,0.001272228,0.0007716287,0.00001324417,0.00007825922,0.004681666],"genre_scores_gemma":[0.9839528,0.00005393155,0.00009389504,0.0002746664,0.00004146933,0.00003772311,0.000003572087,0.000006842723,0.01553516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3584473,"threshold_uncertainty_score":0.5549259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09937112948378411,"score_gpt":0.3655412427002712,"score_spread":0.2661701132164871,"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."}}