{"id":"W3097787131","doi":"10.22541/au.158359887.75671757","title":"Evolutionary dynamics and diversification in changing environments","year":2020,"lang":"en","type":"dataset","venue":"Authorea","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Environmental change; Diversification (marketing strategy); Evolutionary dynamics; Competition (biology); Abiotic component; Biology; Extinction (optical mineralogy); Ecology; Population; Logistic function; Diversity (politics); Evolutionary biology; Climate change; Demography; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0003519052,0.0001022297,0.0001123594,0.0001845119,0.0003757336,0.00002514381,0.0001573312,0.0002029029,0.0001270954],"category_scores_gemma":[0.000100569,0.0001209783,0.00002162676,0.0003064981,0.0001769358,0.0001749534,0.00008848843,0.0001987444,0.0002150079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003129783,"about_ca_system_score_gemma":0.00007185726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004932145,"about_ca_topic_score_gemma":0.001008376,"domain_scores_codex":[0.9989672,0.0002481182,0.000131988,0.0002470367,0.0002208739,0.0001847345],"domain_scores_gemma":[0.9996772,0.00005621367,0.00007241802,0.0001154524,0.00000836888,0.00007030002],"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":[0.00002302447,0.00005088914,0.0003402033,0.00001936015,0.00001134336,0.00001110985,0.00239771,0.00001825013,0.000003763404,0.040946,0.9544019,0.001776463],"study_design_scores_gemma":[0.00009770901,0.0000201056,0.002516392,0.00003024175,0.00002248619,8.505218e-7,0.001835795,0.000659896,3.745089e-7,0.001792944,0.9928632,0.0001600381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005673384,0.0002342088,0.0001692524,0.001677541,0.0002510987,0.0002951055,0.995889,0.00002498659,0.0008914796],"genre_scores_gemma":[0.01760414,0.00131587,0.00003976,0.0001186942,0.0001857193,0.00002105403,0.9797155,0.000005435673,0.0009938761],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03915305,"threshold_uncertainty_score":0.4933352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0170120448842848,"score_gpt":0.2657485944150144,"score_spread":0.2487365495307295,"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."}}