{"id":"W2963391516","doi":"10.1101/707927","title":"Instability of cooperation in finite populations","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada; Ontario Trillium Foundation","keywords":"Population; Evolutionarily stable strategy; Evolutionary game theory; Outcome (game theory); Population size; Selection (genetic algorithm); Mathematical economics; Game theory; Equilibrium selection; Mathematics; Computer science; Repeated game; Artificial intelligence; Demography","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":[0.001968148,0.0002035026,0.0006668298,0.0009222539,0.0008390404,0.001903899,0.0008239025,0.0008917914,0.001584681],"category_scores_gemma":[0.01183012,0.0001975315,0.0004149596,0.0003254126,0.003259049,0.001937703,0.001697955,0.001075124,0.0001766986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517339,"about_ca_system_score_gemma":0.0006647162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001286462,"about_ca_topic_score_gemma":0.0004899907,"domain_scores_codex":[0.9987547,0.0006294217,0.00004385529,0.0001763035,0.0002664041,0.0001293066],"domain_scores_gemma":[0.9922618,0.005198816,0.0009454633,0.0005762401,0.0006055352,0.0004121476],"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":[0.0001014806,0.00005063722,0.005615105,0.00009369183,0.00007706306,0.0004774878,0.0007315536,0.1644994,0.01463733,0.8037938,0.001501858,0.008420649],"study_design_scores_gemma":[0.00002066909,0.00004549749,0.00169112,0.00002700055,0.00001583211,0.000193261,0.0002068913,0.4631963,0.001836832,0.5317082,0.001031367,0.00002711033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7728899,0.0004529538,0.1984499,0.001583993,0.00007048444,0.00003588777,0.00005818365,0.0001986946,0.02626003],"genre_scores_gemma":[0.9968504,0.00004831116,0.002396444,0.00007916832,0.00001360767,0.00002013388,0.00001267628,0.00000929721,0.0005698689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001968148,"threshold_uncertainty_score":0.01100916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03016605367413143,"score_gpt":0.2722556135872332,"score_spread":0.2420895599131018,"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."}}