{"id":"W2892334372","doi":"10.1007/s10661-018-6950-6","title":"An expanded fish-based index of biotic integrity for Great Lakes coastal wetlands","year":2018,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Windsor","funders":"Central Michigan University; University of Notre Dame; U.S. Environmental Protection Agency; National Science Foundation","keywords":"Ibis; Index of biological integrity; Wetland; Environmental science; Water quality; Vegetation (pathology); Abiotic component; Biotic index; Ecosystem; Biological integrity; Habitat; Ecology; Hydrology (agriculture); Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005759452,0.0003232651,0.0002319008,0.002005053,0.0003561116,0.0003855364,0.000318254,0.0001537041,0.001560668],"category_scores_gemma":[0.001387002,0.0001002267,0.0003223271,0.00143958,0.0001985593,0.0005026245,0.0005970604,0.0002990094,0.0002060994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007308964,"about_ca_system_score_gemma":0.0004298245,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01968972,"about_ca_topic_score_gemma":0.07788235,"domain_scores_codex":[0.9997362,0.00003729554,0.00003930496,0.00004216018,0.0001169144,0.00002799857],"domain_scores_gemma":[0.9989631,0.0000786202,0.0004674917,0.00007383488,0.000308505,0.0001083996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004834342,0.00004850256,0.9748874,0.00003300932,0.00009273615,0.00004094785,0.0001414318,0.001121498,0.002543033,0.00009660082,0.0006791244,0.02026735],"study_design_scores_gemma":[0.000002032346,0.00004220473,0.9970791,0.000003494608,0.00000811397,0.00004401986,0.00005006069,0.001983345,0.0003011722,0.00004031803,0.0004407867,0.000005413809],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891365,0.00008323629,0.003718647,0.00002727421,0.000006131126,0.0001230245,0.004582662,0.00006070227,0.002261928],"genre_scores_gemma":[0.984488,0.00005698321,0.009563351,0.00001541178,0.000008903903,0.0002289985,0.004593366,0.000009077949,0.001036108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9803103,"threshold_uncertainty_score":0.03915018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02057166511727732,"score_gpt":0.2948999526919278,"score_spread":0.2743282875746505,"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."}}