{"id":"W3137621289","doi":"10.1101/2021.03.21.436334","title":"Origin of diversity in spatial social dilemmas","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diversification (marketing strategy); Evolutionary dynamics; Population; Trait; Fitness landscape; Evolutionary biology; Biology; Diversity (politics); Adaptive evolution; Computer science; Genetics; Sociology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001231735,0.0002238702,0.000395469,0.0001657704,0.0006137933,0.00008586369,0.0004853974,0.0004963721,0.0002760859],"category_scores_gemma":[0.00025899,0.0002846833,0.0001310625,0.0005329609,0.0003376772,0.0002340756,0.0007344265,0.0005136712,0.00001418911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004445424,"about_ca_system_score_gemma":0.001374458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005226873,"about_ca_topic_score_gemma":0.001231453,"domain_scores_codex":[0.9975792,0.0006823048,0.0003642655,0.0005023489,0.0005161564,0.0003557748],"domain_scores_gemma":[0.9987668,0.0000697643,0.0002657,0.0003290258,0.0004628781,0.0001058758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003633364,0.001705888,0.4745791,0.000941888,0.0003150233,0.0002725901,0.008329017,0.0006364571,0.2045836,0.3075943,0.0006413398,0.00003742224],"study_design_scores_gemma":[0.001051171,0.00005711223,0.9664565,0.0004689289,0.0001530816,3.147431e-9,0.0004070506,0.0001759415,0.02485349,0.0001182166,0.004983587,0.001274896],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970738,0.0002235392,0.0007571686,0.000327977,0.0009445466,0.0003332139,0.00007531763,0.0001017321,0.0001627173],"genre_scores_gemma":[0.9987257,0.0001381087,0.0003672106,0.00005312219,0.0006538874,0.00002773009,5.332523e-7,0.00002106453,0.00001270053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4918774,"threshold_uncertainty_score":0.9999605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03479157728398069,"score_gpt":0.2653725084027904,"score_spread":0.2305809311188097,"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."}}