{"id":"W2087014302","doi":"10.1139/f03-043","title":"Watershed, reach, and riparian influences on stream fish assemblages in the Northern Lakes and Forest Ecoregion, U.S.A.","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":265,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Maryland Department of Natural Resources; Michigan Department of Natural Resources; Rural Development Administration; U.S. Environmental Protection Agency","keywords":"Ecoregion; Riparian zone; Watershed; STREAMS; Environmental science; Ecology; Macrophyte; Percidae; Wetland; Predatory fish; Hydrology (agriculture); Fishery; Fish <Actinopterygii>; Biology; Habitat; Perch; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007531774,0.00009025628,0.0001251979,0.00007172679,0.0005013451,0.000158993,0.0001620355,0.00002884362,0.00004314144],"category_scores_gemma":[0.000219502,0.00005398275,0.00001259711,0.0001549656,0.001344638,0.0003205527,0.00001627063,0.0000829467,0.000001218624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001979717,"about_ca_system_score_gemma":0.00003967656,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00384773,"about_ca_topic_score_gemma":0.7230344,"domain_scores_codex":[0.9992658,0.00008098695,0.0001660209,0.0001420794,0.0001296638,0.000215373],"domain_scores_gemma":[0.9995872,0.0001498084,0.00009002481,0.0000563359,0.00000433353,0.00011233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002206541,0.000006018708,0.9927157,0.000003253825,0.000005686788,0.00002450915,0.002367031,0.00002241876,0.000001555541,0.0003397026,0.003242302,0.00126963],"study_design_scores_gemma":[0.0001552507,0.0002670702,0.9776682,0.0000210638,0.00001182808,0.00004217577,0.008819193,0.00004614916,0.000003554568,0.004816026,0.008069337,0.00008011886],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828316,0.0001049086,0.00000233673,0.009355392,0.00006779394,0.00007180353,7.197789e-7,0.000001206664,0.007564266],"genre_scores_gemma":[0.9980967,0.0002076385,0.00006483351,0.001526988,0.00001087226,0.00000276896,1.986574e-7,0.000001967529,0.00008804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7191867,"threshold_uncertainty_score":0.5816643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415727462387497,"score_gpt":0.2018535829691746,"score_spread":0.1876963083452996,"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."}}