{"id":"W3120642889","doi":"10.1098/rspb.2020.2483","title":"Whose trait is it anyways? Coevolution of joint phenotypes and genetic architecture in mutualisms","year":2021,"lang":"en","type":"article","venue":"Proceedings of the Royal Society B Biological Sciences","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Integrative Organismal Systems; Natural Sciences and Engineering Research Council of Canada; Division of Environmental Biology; Radcliffe Institute for Advanced Study, Harvard University; National Institute of Food and Agriculture","keywords":"Trait; Evolvability; Genetic architecture; Mutualism (biology); Coevolution; Biology; Evolutionary biology; Genetic Fitness; Adaptation (eye); Genome; Epistasis; Experimental evolution; Quantitative trait locus; Genetics; Ecology; Computer science; Biological evolution; 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":[0.001009272,0.0002130681,0.0006165155,0.0004323122,0.0008431713,0.002051816,0.0003448361,0.0007956768,0.0009910375],"category_scores_gemma":[0.003471649,0.000222836,0.0004990339,0.0006105612,0.001822716,0.001675292,0.001023975,0.0007784164,0.0001711565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006444582,"about_ca_system_score_gemma":0.0003159983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001815386,"about_ca_topic_score_gemma":0.002446007,"domain_scores_codex":[0.9994571,0.0002795683,0.0000183838,0.0001324573,0.00005223385,0.00006036842],"domain_scores_gemma":[0.9991099,0.0003919079,0.0001861656,0.0001020134,0.00005868032,0.0001512269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009162516,0.0002309101,0.5566256,0.0003188557,0.001004973,0.00249942,0.004261606,0.06513481,0.1366267,0.1483525,0.001297276,0.08273115],"study_design_scores_gemma":[0.00007747426,0.0003041224,0.4921804,0.00007783328,0.0003759926,0.002075108,0.003004813,0.1396726,0.006912852,0.3481832,0.006845666,0.0002898986],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844929,0.0004383549,0.0119101,0.0008871629,0.00001259212,0.000005345389,0.000051332,0.00003631022,0.002165999],"genre_scores_gemma":[0.9980926,0.00009527298,0.001531242,0.00008010709,0.000003435309,0.000003388629,0.00001832099,0.000009439259,0.0001660972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002051816,"threshold_uncertainty_score":0.005337596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0547136286536471,"score_gpt":0.2187202678591798,"score_spread":0.1640066392055327,"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."}}