{"id":"W3166851616","doi":"10.1111/ele.13814","title":"Multiple Mutualism Effects generate synergistic selection and strengthen fitness alignment in the interaction between legumes, rhizobia and mycorrhizal fungi","year":2021,"lang":"en","type":"article","venue":"Ecology Letters","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Agriculture","keywords":"Mutualism (biology); Biology; Rhizobia; Medicago truncatula; Trait; Heritability; Coevolution; Ecology; Natural selection; Symbiosis; Evolutionary ecology; Selection (genetic algorithm); Host (biology); Evolutionary biology; Bacteria; 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":[0.0001191348,0.00009564198,0.0001347895,0.000009432739,0.0001921629,0.0000434512,0.00005021491,0.00005238326,0.00002007427],"category_scores_gemma":[0.00005394076,0.00003883314,0.00002006865,0.00009897158,0.00003140492,0.00006438034,0.00004908194,0.0001065271,0.000004239299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002232295,"about_ca_system_score_gemma":0.000001980728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002056761,"about_ca_topic_score_gemma":0.008175188,"domain_scores_codex":[0.9992732,0.0001837626,0.0001055217,0.0002075348,0.00005605852,0.0001738722],"domain_scores_gemma":[0.9989588,0.000956315,0.00003814929,0.00001242492,0.00001026731,0.00002408857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000205761,0.00003037222,0.6886818,0.000008821449,0.00003273247,0.00004690136,0.0002404829,0.00001040288,0.3058954,0.00005189784,0.0008175435,0.004163121],"study_design_scores_gemma":[0.0001554146,0.0001192177,0.9950473,0.00001107809,0.00002475048,0.00002361739,0.0002868679,0.0001856054,0.002888942,0.00002475473,0.001138257,0.00009413847],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958749,0.0001696341,0.000002017769,0.003689713,0.0001033576,0.0001055376,0.00001353652,0.00001452818,0.00002671512],"genre_scores_gemma":[0.9986458,0.0001237876,0.00001466029,0.0008983157,0.0002275207,0.00001886528,0.00005211028,6.496821e-7,0.00001824781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3063655,"threshold_uncertainty_score":0.4561947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01995250351193227,"score_gpt":0.204266736169464,"score_spread":0.1843142326575317,"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."}}