{"id":"W4396624576","doi":"10.1007/s11538-024-01296-y","title":"Evolution of Cooperation in Spatio-Temporal Evolutionary Games with Public Goods Feedback","year":2024,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canada Research Chairs","keywords":"Replicator equation; Public goods game; Evolutionary game theory; Population; Stability (learning theory); Computer science; Bistability; Evolutionarily stable strategy; Diffusion; Game theory; Ecology; Public good; Mathematical economics; Microeconomics; Economics; Biology; Physics","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":[0.001127973,0.0001021371,0.000237283,0.0001563016,0.00008790786,0.00001530514,0.0001452402,0.0001660689,0.002454104],"category_scores_gemma":[0.0004795897,0.0000819845,0.00004863694,0.0003877689,0.0009233953,0.00008521954,0.0000298028,0.0001202898,0.0001192947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001356095,"about_ca_system_score_gemma":0.0003475746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003077549,"about_ca_topic_score_gemma":0.0003259842,"domain_scores_codex":[0.9984576,0.0005130163,0.0004264764,0.0002131363,0.0001801704,0.0002095862],"domain_scores_gemma":[0.9991527,0.0004287423,0.00008497092,0.0001270101,0.0001569565,0.00004959773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007353602,0.0001754036,0.002617669,0.0001017556,0.00001586016,0.000001467937,0.001000789,0.00005200069,0.000304446,0.9937922,0.001148079,0.0007167287],"study_design_scores_gemma":[0.001707087,0.002137216,0.01083249,0.001392622,0.0001019143,0.00004731013,0.009378721,0.008406408,0.0007926844,0.7037989,0.2605231,0.0008814153],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8760986,0.002807851,0.03161277,0.01935774,0.0002867742,0.0009266803,0.00004662825,0.0001840932,0.0686789],"genre_scores_gemma":[0.9957591,0.00004752463,0.003113979,0.00002520018,0.00008534497,0.00003424977,0.00004324945,0.00000815545,0.0008832118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2899933,"threshold_uncertainty_score":0.9984578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799863277144733,"score_gpt":0.2779627440588993,"score_spread":0.259964111287452,"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."}}