{"id":"W2337704952","doi":"10.1111/eva.12384","title":"Genetic consequences of selection cutting on sugar maple (<i>Acer saccharum</i>Marshall)","year":2016,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Genetic diversity; Selection (genetic algorithm); Inbreeding; Maple; Saccharum; Species richness; Genetic erosion; Genetic gain; Genetic variation; Ecology; Botany; Population; Demography; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003043451,0.0001681941,0.0001233122,0.000390805,0.0004391111,0.0002603008,0.0001962895,0.0001453149,0.0007094757],"category_scores_gemma":[0.0004511937,0.00004863317,0.0001101408,0.0002973551,0.0003225398,0.00007795774,0.0001603199,0.0002583574,0.00004947475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001887145,"about_ca_system_score_gemma":0.0009169246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2059287,"about_ca_topic_score_gemma":0.4744812,"domain_scores_codex":[0.9998482,0.00003108582,0.000005984711,0.00003655233,0.00003347896,0.0000446713],"domain_scores_gemma":[0.9994816,0.0001189919,0.0001323309,0.000019855,0.0001109029,0.0001362444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007435809,0.0002408739,0.8053262,0.00004168564,0.0001732511,0.001018361,0.000713081,0.001651592,0.1740752,0.0002403936,0.0003121497,0.01546365],"study_design_scores_gemma":[0.000002973042,0.00006993962,0.9981274,0.000001997443,0.00001059061,0.00006422147,0.0001455324,0.0003712317,0.001081309,0.00001584737,0.0001048994,0.000004024098],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998029,0.00001504367,0.00002763714,0.000004692015,5.067811e-7,0.000001591117,0.00003987707,9.153222e-7,0.0001069478],"genre_scores_gemma":[0.9996032,0.00001845215,0.00008144211,0.0000107318,6.054329e-7,0.000001991339,0.00009902126,0.000001198539,0.0001834493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2059287,"threshold_uncertainty_score":0.4094602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009894820167685527,"score_gpt":0.2315595833589507,"score_spread":0.2216647631912652,"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."}}