{"id":"W4296613313","doi":"10.1111/gcb.16439","title":"Fish and macroinvertebrate assemblages reveal extensive degradation of the world's rivers","year":2022,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Environment and Climate Change Canada; University of Waterloo","funders":"Fundação para a Ciência e a Tecnologia; Australian Research Council; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Biodiversity; Water quality; Climate change; Environmental science; Geography; Ecology; Arid; Biota; Freshwater ecosystem; Physical geography; Environmental protection; Ecosystem; Biology","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":[0.0003807041,0.0001721187,0.0002217284,0.001132479,0.0002893594,0.0005145145,0.0001547538,0.0002695768,0.0005578689],"category_scores_gemma":[0.0008083897,0.0001910274,0.0001939518,0.001390747,0.0005307809,0.0005371522,0.0007363829,0.0001869452,0.00009453633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002325101,"about_ca_system_score_gemma":0.0002015027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01139726,"about_ca_topic_score_gemma":0.02349196,"domain_scores_codex":[0.9996624,0.00008167709,0.00004821748,0.00009320596,0.00006660228,0.00004781771],"domain_scores_gemma":[0.9993542,0.00006807967,0.0003452117,0.00006933977,0.0000923964,0.00007074529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002382205,0.000006876418,0.995966,0.00001196141,0.00002848563,0.0000397842,0.0003307804,0.00004743285,0.0007710751,0.00001202401,0.00005754524,0.002704258],"study_design_scores_gemma":[3.781584e-7,0.00001036486,0.9995841,0.00000194705,0.000004084127,0.00004426689,0.0002254974,0.0000265321,0.00002930853,0.000005892921,0.0000665716,0.000001043189],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994135,0.0000983946,0.00003775441,0.00001169804,5.60123e-7,0.000002074616,0.0001895381,0.000002237925,0.0002442554],"genre_scores_gemma":[0.9994454,0.00009643126,0.0001078109,0.00001200608,0.000002271853,0.000003988016,0.0002495057,7.745588e-7,0.00008189465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01139726,"threshold_uncertainty_score":0.02266186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02143676588295495,"score_gpt":0.2417862324908523,"score_spread":0.2203494666078973,"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."}}