{"id":"W2158673360","doi":"10.1111/j.1461-0248.2009.01350.x","title":"Evolutionary rescue can prevent extinction following environmental change","year":2009,"lang":"en","type":"article","venue":"Ecology Letters","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":616,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Extinction (optical mineralogy); Environmental change; Maladaptation; Population; Population size; Biology; Experimental evolution; Ecology; Biodiversity; Effective population size; Small population size; Evolutionary biology; Evolutionary dynamics; Population growth; Climate change; Genetic variation; Demography; Genetics; Habitat","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":[0.0000773904,0.0001118406,0.00008416409,0.00003788958,0.0001060214,0.000004813497,0.00009888669,0.0001233701,0.00004784805],"category_scores_gemma":[0.00001100885,0.0001245269,0.0001026972,0.00003133279,0.00004590391,0.000003261198,0.00004091456,0.0000766624,0.00002574463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008583786,"about_ca_system_score_gemma":0.00001547949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006700367,"about_ca_topic_score_gemma":0.00009529692,"domain_scores_codex":[0.9992219,0.00006344978,0.0001289406,0.000270527,0.00007637727,0.0002388438],"domain_scores_gemma":[0.9997082,0.000003647755,0.00003602904,0.0001900972,0.000003732688,0.00005828806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005716985,0.0002869199,0.06589527,0.000003555275,0.0001067927,0.00003040171,0.0001253943,0.0008822755,0.9155004,0.00003569534,0.01362851,0.003447636],"study_design_scores_gemma":[0.0006512739,0.0004658502,0.9782501,0.000003953165,0.0000375087,0.00004794908,0.00004894961,0.001094628,0.00237435,0.00006475708,0.0166881,0.000272525],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922265,0.0002244955,0.0005399522,0.006201209,0.0004059781,0.0001923024,0.0000104317,0.00001719054,0.0001819008],"genre_scores_gemma":[0.9891161,0.00006500566,0.0005100511,0.009244647,0.0003101849,0.00002298584,0.0002755561,0.000009898684,0.0004455255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9131261,"threshold_uncertainty_score":0.5078059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005551323963901717,"score_gpt":0.2115414084523438,"score_spread":0.2059900844884421,"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."}}