{"id":"W2774339346","doi":"10.1111/brv.12366","title":"Comparing species interaction networks along environmental gradients","year":2017,"lang":"en","type":"review","venue":"Biological reviews/Biological reviews of the Cambridge Philosophical Society","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":309,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Consejo Nacional para Investigaciones Científicas y Tecnológicas; Ministerio de Ciencia y Tecnología; Natural Environment Research Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Agence Nationale de la Recherche; Deutscher Akademischer Austauschdienst; Sight Research UK","keywords":"Modularity (biology); Variation (astronomy); Null model; Trait; Nestedness; Ecological network; Ecology; Matching (statistics); Abiotic component; Standardization; Computer science; Biology; Species richness; Evolutionary biology; Mathematics; Ecosystem; Statistics","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":[0.00404613,0.0003865858,0.0006499515,0.004953819,0.0005014218,0.001430115,0.0006905289,0.0005391082,0.001874198],"category_scores_gemma":[0.01491085,0.0002583151,0.001226823,0.003826817,0.001081165,0.002967249,0.001198279,0.0007559115,0.0002398947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009731478,"about_ca_system_score_gemma":0.0006542644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001623857,"about_ca_topic_score_gemma":0.003363336,"domain_scores_codex":[0.99657,0.001836178,0.0002354885,0.0008291893,0.0004106288,0.0001185822],"domain_scores_gemma":[0.9835106,0.01235709,0.002232213,0.0007296506,0.0009393851,0.0002310499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001105644,0.0001375658,0.2949623,0.023538,0.01083535,0.0007343607,0.005472874,0.05661969,0.02779585,0.1255742,0.006841947,0.4463822],"study_design_scores_gemma":[0.00006818892,0.0005299471,0.6765873,0.001907736,0.003261895,0.001005918,0.002772799,0.04292851,0.008117293,0.1945157,0.06809544,0.0002092986],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.7407848,0.07677712,0.1542403,0.001351915,0.0002415576,0.0002133121,0.008598057,0.0004964051,0.01729653],"genre_scores_gemma":[0.9397322,0.01909556,0.03423494,0.0002550766,0.0001051103,0.000300423,0.005211799,0.00009771825,0.0009672742],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004953819,"threshold_uncertainty_score":0.02139825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4573252290690971,"score_gpt":0.3355773081585651,"score_spread":0.121747920910532,"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."}}