{"id":"W4403265016","doi":"10.1007/s00285-024-02145-1","title":"Evolutionary branching in multi-level selection models","year":2024,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Branching (polymer chemistry); Selection (genetic algorithm); Evolutionary biology; Mathematics; Biology; Branching process; Econometrics; Mathematical economics; Statistical physics; Computer science; Statistics; Artificial intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003795133,0.00008844026,0.0001575784,0.0001187694,0.00002091809,0.00001126488,0.0001071317,0.0001660951,0.00003383838],"category_scores_gemma":[0.0001357117,0.00006943951,0.0001043178,0.0001008514,0.00005483444,0.000006879172,0.00003826282,0.0001856004,0.00001403212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003200061,"about_ca_system_score_gemma":0.00009991557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001367847,"about_ca_topic_score_gemma":0.000009568906,"domain_scores_codex":[0.9991904,0.00007746961,0.0003819286,0.0001305901,0.00006879136,0.0001507527],"domain_scores_gemma":[0.9997022,0.00003755231,0.00006644896,0.0000708388,0.00006967699,0.00005328618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002591543,0.0008410522,0.00247084,0.0003512822,0.0003284641,0.00004589753,0.0004281289,0.02239891,0.8264952,0.1256831,0.004786375,0.01591164],"study_design_scores_gemma":[0.001427007,0.0009623161,0.004472742,0.000278927,0.00005386079,0.001867603,0.0001278496,0.7627062,0.003366745,0.2178022,0.006545099,0.0003894778],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2536748,0.002440316,0.7426892,0.0003426645,0.0002222346,0.00006413143,0.000008063937,0.000007677948,0.0005509531],"genre_scores_gemma":[0.9606661,0.0002053589,0.0385358,0.00008784717,0.0001517258,0.000002330005,0.000008765783,0.00001098494,0.0003311365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8231284,"threshold_uncertainty_score":0.2831661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03900854411137697,"score_gpt":0.3190011795768508,"score_spread":0.2799926354654738,"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."}}