{"id":"W3202783444","doi":"10.3390/w13192732","title":"Riparian Land Cover, Water Temperature Variability, and Thermal Stress for Aquatic Species in Urban Streams","year":2021,"lang":"en","type":"article","venue":"Water","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Northern Research Station; Fonds de recherche du Québec – Nature et technologies; U.S. Forest Service; U.S. Department of Agriculture","keywords":"Impervious surface; Environmental science; Riparian zone; Stormwater; Hydrology (agriculture); STREAMS; Thermal pollution; Water quality; Canopy; Surface runoff; Land cover; Habitat; Ecology; Land use; Environmental engineering; Geology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001776828,0.0000909791,0.0001230835,0.00001144723,0.0001055752,0.00003599291,0.00006394397,0.00005620658,0.00189372],"category_scores_gemma":[0.00001475486,0.00005232417,0.00001923354,0.00002331757,0.0001035785,0.0001141289,0.0002647066,0.00006311187,0.00008761896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002748176,"about_ca_system_score_gemma":0.000001458655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004882998,"about_ca_topic_score_gemma":0.001976743,"domain_scores_codex":[0.9993038,0.00004904778,0.0001041805,0.0002360455,0.0000629779,0.0002439614],"domain_scores_gemma":[0.9998074,0.00003403484,0.000008348456,0.0001248948,0.000002916009,0.00002245225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002117092,0.0001004184,0.9835737,0.00003032626,0.00002556653,0.00001781178,0.001727912,0.0001792807,0.006355098,0.00006532147,0.00783921,0.00006416599],"study_design_scores_gemma":[0.001253835,0.00007492832,0.9145625,0.00001332715,0.00003933828,0.000002104459,0.0002345992,0.0003033257,0.04567805,0.002033691,0.03555498,0.0002493648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882061,0.00000692146,0.000007177396,0.002415804,0.0001113956,0.0001917275,0.00001122363,0.00001012604,0.009039477],"genre_scores_gemma":[0.9882424,0.00001017675,0.00008076159,0.0004735909,0.0000352293,0.00003585304,0.00004717934,0.000005792881,0.01106903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06901126,"threshold_uncertainty_score":0.9990187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006047268654770815,"score_gpt":0.1886508815518017,"score_spread":0.1826036128970309,"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."}}