{"id":"W2950090944","doi":"10.1086/700118","title":"Evolutionary Responses to Conditionality in Species Interactions across Environmental Gradients","year":2018,"lang":"en","type":"article","venue":"The American Naturalist","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Conditionality; Ecology; Biology; Environmental gradient; Evolutionary biology; Geography; Political science; Habitat","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003028533,0.000298427,0.0004137399,0.0005097667,0.0006166118,0.0009796927,0.0008232222,0.0006592187,0.002418157],"category_scores_gemma":[0.01458118,0.0002993631,0.0004826726,0.0003980656,0.001547389,0.001083172,0.001674695,0.001129813,0.0001111947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008255233,"about_ca_system_score_gemma":0.0003528059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001717882,"about_ca_topic_score_gemma":0.003392326,"domain_scores_codex":[0.9985246,0.0007932848,0.00006194246,0.0003870077,0.000125627,0.0001076356],"domain_scores_gemma":[0.9916245,0.005156656,0.001636502,0.0008034912,0.0003122989,0.0004664557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009409065,0.0003980137,0.4405886,0.0003517483,0.0008668649,0.0008131273,0.001682543,0.3380865,0.08237926,0.08924335,0.001113872,0.04353522],"study_design_scores_gemma":[0.00007343017,0.0004325723,0.2760284,0.00002945455,0.0002028495,0.0004245116,0.0006873046,0.6210586,0.005214771,0.09461497,0.001094361,0.0001387393],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820917,0.00004225575,0.01618172,0.0001610804,0.00000607535,0.00001968293,0.00012158,0.00006691671,0.001308943],"genre_scores_gemma":[0.9955599,0.00001825329,0.004111457,0.00004632971,0.000002567755,0.00003622111,0.00006305704,0.00001259363,0.0001495413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003028533,"threshold_uncertainty_score":0.01601654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04318169205892909,"score_gpt":0.2815484132115808,"score_spread":0.2383667211526517,"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."}}