{"id":"W2791137976","doi":"10.1002/ece3.3947","title":"Characterizing the contribution of plasticity and genetic differentiation to community‐level trait responses to environmental change","year":2018,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Université du Québec à Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Intraspecific competition; Biology; Phenotypic plasticity; Trait; Local adaptation; Interspecific competition; Adaptation (eye); Ecology; Genetic variation; Genetic architecture; Evolutionary biology; Environmental change; Quantitative trait locus; Climate change; Genetics; Population; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004249474,0.0001189231,0.0001933554,0.0005068526,0.0001973746,0.0003632975,0.0002024809,0.0002650548,0.0004494729],"category_scores_gemma":[0.0008902373,0.0001128258,0.0001555043,0.0002772934,0.000257202,0.0002475435,0.0003583753,0.0002660009,0.00005504784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002355458,"about_ca_system_score_gemma":0.00009836928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001526376,"about_ca_topic_score_gemma":0.003186156,"domain_scores_codex":[0.9998156,0.00005478803,0.00001033582,0.00006294263,0.00002763841,0.00002859565],"domain_scores_gemma":[0.9993587,0.0002369154,0.0001662196,0.00007334929,0.00008450008,0.00008042172],"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":[0.0003276689,0.0001339164,0.4166663,0.00005165464,0.0001946071,0.00006119795,0.0002603654,0.001466432,0.5709578,0.0001984514,0.00004922343,0.009632404],"study_design_scores_gemma":[0.000002386621,0.00006332608,0.9931903,0.000001604427,0.00001444307,0.00003584627,0.00008202916,0.003728184,0.002729773,0.00008504909,0.00006170193,0.000005295788],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994123,0.00001938903,0.0004192407,0.00000516767,5.114023e-7,0.000002758589,0.00003248195,0.000004770889,0.0001034413],"genre_scores_gemma":[0.9997199,0.000005190493,0.0001896046,0.000006099708,8.943466e-7,0.000003820381,0.0000426384,0.000001665064,0.00003003765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001526376,"threshold_uncertainty_score":0.003034949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0573942706949831,"score_gpt":0.2168316645837187,"score_spread":0.1594373938887356,"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."}}