{"id":"W2114181979","doi":"10.1038/428611a","title":"Cooperate with thy neighbour?","year":2004,"lang":"en","type":"letter","venue":"Nature","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Population; Evolutionary biology; Computer science; Biology; Artificial intelligence; Demography; Sociology","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":["research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0002582732,0.0001905335,0.0001763594,0.00006303026,0.0006038619,0.00012079,0.0003345474,0.004942107,0.0009358494],"category_scores_gemma":[0.00006166594,0.0001471923,0.0000535387,0.0003263245,0.0002516264,0.0002152298,0.00001718972,0.00809586,0.0002252798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002133753,"about_ca_system_score_gemma":0.0008612852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001486589,"about_ca_topic_score_gemma":0.0005322282,"domain_scores_codex":[0.9984542,0.0002619998,0.0001040751,0.0003008852,0.000548601,0.0003302481],"domain_scores_gemma":[0.9993589,0.00006733397,0.00007218339,0.0002089989,0.0002458116,0.00004675765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002454494,0.00001149968,0.00001745837,0.00001581552,0.00002665143,0.0001608553,0.0009996761,0.00005548364,0.000004585028,0.07823999,0.9202027,0.0002406842],"study_design_scores_gemma":[0.0001707078,0.00004990794,0.00004122798,0.0000780101,0.00002670994,0.000007315592,0.0001043104,0.000001211982,0.00001137056,0.00479941,0.9944721,0.0002376747],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0005314485,0.001267502,0.0000508881,0.8704081,0.0007172553,0.000286782,0.00003416315,0.0001525111,0.1265513],"genre_scores_gemma":[0.0375561,0.0001336766,0.0001353757,0.8917831,0.008887578,0.00002239782,0.0003277658,0.00003276149,0.0611213],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.07426939,"threshold_uncertainty_score":0.9999774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00743277233019279,"score_gpt":0.2630651188349896,"score_spread":0.2556323465047968,"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."}}