{"id":"W2173181414","doi":"10.3394/0380-1330(2007)33[172:uadotw]2.0.co;2","title":"Use and Development of the Wetland Macrophyte Index to Detect Water Quality Impairment in Fish Habitat of Great Lakes Coastal Marshes","year":2007,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":86,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Wetland; Marsh; Macrophyte; Habitat; Water quality; Environmental science; Bay; Ecology; Indicator species; Aquatic plant; Index of biological integrity; Ecosystem; Fishery; Geography; Hydrology (agriculture); Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002914512,0.0001298738,0.0002833434,0.0002001778,0.0001141324,0.00004348152,0.0003473263,0.00007029868,0.00004386546],"category_scores_gemma":[0.0001089913,0.00007105521,0.00007046208,0.0003162709,0.0003766891,0.0002191767,0.0004906725,0.00031128,0.000004453951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002057963,"about_ca_system_score_gemma":0.00004055641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004832344,"about_ca_topic_score_gemma":0.01739357,"domain_scores_codex":[0.9972749,0.0002339447,0.0006942872,0.0001773007,0.001158749,0.0004608681],"domain_scores_gemma":[0.9991746,0.0002147632,0.0001310424,0.000202952,0.0001019967,0.0001746291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007088404,0.00008670633,0.9777064,0.00004253264,0.00002144832,0.00003367908,0.002058082,0.0001306114,0.01184621,8.704969e-7,0.0001122888,0.007252322],"study_design_scores_gemma":[0.0007014027,0.0002988254,0.9456564,0.00009930577,0.000004045795,0.00003222001,0.0004166305,0.00003076435,0.05130283,0.0002539342,0.001113213,0.00009044111],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992033,0.00001357755,0.00008561159,0.0002939139,0.00006362235,0.0002226953,0.00001436954,0.000002007926,0.000100964],"genre_scores_gemma":[0.9989931,0.00003394598,0.0007280704,0.00002841245,0.00002080562,0.000002722118,0.000001155872,0.0000100784,0.0001817281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03945662,"threshold_uncertainty_score":0.9706019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04409959224904484,"score_gpt":0.3092519337220233,"score_spread":0.2651523414729784,"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."}}