{"id":"W2514283143","doi":"10.1038/s41598-017-07621-x","title":"Strategic tradeoffs in competitor dynamics on adaptive networks","year":2017,"lang":"en","type":"preprint","venue":"Scientific Reports","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Santa Fe Institute; James S. McDonnell Foundation; Defense Threat Reduction Agency; National Science Foundation","keywords":"Competition (biology); Transitive relation; Stochastic game; Outcome (game theory); Evolutionary dynamics; Evolutionary game theory; Game theory; Dynamics (music); Social network (sociolinguistics); Conversation; Social dynamics; Politics; Computer science; Microeconomics; Economics; Sociology; Political science; Artificial intelligence; Social media; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002108273,0.0006259221,0.0007316466,0.001470605,0.001699856,0.003572223,0.001071513,0.00225396,0.008258169],"category_scores_gemma":[0.01444078,0.0005045345,0.0007407262,0.0006489401,0.003074439,0.005372092,0.002262005,0.001095225,0.0005559074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001762805,"about_ca_system_score_gemma":0.0004926308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001985436,"about_ca_topic_score_gemma":0.001877929,"domain_scores_codex":[0.9982773,0.000838689,0.0000572243,0.0003734443,0.0002487022,0.0002046387],"domain_scores_gemma":[0.9925733,0.004503286,0.001152182,0.0004772093,0.000408695,0.0008852615],"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":[0.00006359676,0.00003173807,0.002763576,0.00007164505,0.00004827963,0.0002962646,0.0006064392,0.05138235,0.003673434,0.9333929,0.001031942,0.006637823],"study_design_scores_gemma":[0.00004409795,0.00006793853,0.0021874,0.00002551721,0.00003069369,0.000291855,0.0004382671,0.3356247,0.0004939871,0.6570476,0.003706623,0.00004134433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6820011,0.0006229254,0.2612837,0.002694149,0.00007664193,0.0001248416,0.0002362085,0.0001594565,0.05280094],"genre_scores_gemma":[0.9845761,0.0002083803,0.01102126,0.0001121538,0.00003382498,0.00007750373,0.00005853302,0.00002988964,0.003882421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008258169,"threshold_uncertainty_score":0.02762634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03244627617956254,"score_gpt":0.2908604834136349,"score_spread":0.2584142072340724,"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."}}