{"id":"W1678464877","doi":"10.1111/j.1752-4571.2010.00169.x","title":"Eco‐evolutionary effects on population recovery following catastrophic disturbance","year":2011,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Biology; Disturbance (geology); Evolutionary dynamics; Population; Natural selection; Microevolution; Experimental evolution; Ecology; Persistence (discontinuity); Threatened species; Adaptation (eye); Trait; Genetic Fitness; Status quo; Evolutionary biology; Biological evolution; Demography; Genetics","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":[0.00005726289,0.0001673577,0.0001112275,0.00007238974,0.0003740483,0.000009290448,0.0002114321,0.0001529533,0.00005976525],"category_scores_gemma":[0.0000260845,0.000185782,0.0001452019,0.0001776898,0.00004063002,0.00001453044,0.00007787074,0.0001033732,0.0001396477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005112975,"about_ca_system_score_gemma":0.00003940783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005695226,"about_ca_topic_score_gemma":0.000007708796,"domain_scores_codex":[0.9989467,0.00005829862,0.0001872285,0.000427075,0.0001750288,0.0002056313],"domain_scores_gemma":[0.9992782,0.00001777231,0.0000959029,0.000465315,0.00005118912,0.00009157802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001032241,0.001372918,0.7609601,0.0002231164,0.0008151436,0.00002461912,0.0003886261,0.006678026,0.04488339,0.05293847,0.08635335,0.04432998],"study_design_scores_gemma":[0.0003265887,0.0001765283,0.9500737,0.00001491347,0.00004321387,0.00001313891,0.00001900429,0.00004611106,0.001379255,0.005595638,0.04204875,0.0002631708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9516926,0.001681631,0.03530003,0.0002651149,0.0008010766,0.001255877,0.0003054096,0.000126994,0.008571248],"genre_scores_gemma":[0.9867421,0.00004036617,0.00922229,0.0002264237,0.0003530087,0.0001762611,0.002190316,0.00001786674,0.001031299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1891136,"threshold_uncertainty_score":0.7575971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008828077415340894,"score_gpt":0.2132153747615278,"score_spread":0.2043872973461869,"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."}}