{"id":"W2137566136","doi":"10.1577/m08-251.1","title":"Evaluation of a Simple Method to Classify the Thermal Characteristics of Streams Using a Nomogram of Daily Maximum Air and Water Temperatures","year":2009,"lang":"en","type":"article","venue":"North American Journal of Fisheries Management","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Ministry of Natural Resources and Forestry; Trent University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"STREAMS; Environmental science; Air temperature; Surface runoff; Hydrology (agriculture); Groundwater; Sampling (signal processing); Nomogram; Surface water; Structural basin; Ecology; Meteorology; Geography; Geology; Environmental engineering; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00985898,0.001277703,0.001030902,0.004483466,0.0007288338,0.002391247,0.001266697,0.0007789611,0.001414386],"category_scores_gemma":[0.02410056,0.0003741197,0.0009132091,0.003019347,0.000446033,0.001334119,0.001022795,0.0006245774,0.0004565487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001210428,"about_ca_system_score_gemma":0.0009508903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008302097,"about_ca_topic_score_gemma":0.01157724,"domain_scores_codex":[0.9949501,0.002765343,0.0003571302,0.0006157744,0.001174102,0.0001376024],"domain_scores_gemma":[0.9781243,0.01421223,0.001829836,0.0009442903,0.004427026,0.0004623538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001815963,0.0009892259,0.3427722,0.0007120378,0.0008411022,0.0002296835,0.0009860442,0.07449916,0.009640218,0.001605019,0.00389252,0.5620168],"study_design_scores_gemma":[0.0001730622,0.001203278,0.2031231,0.0001036576,0.0002086959,0.0002541568,0.001259765,0.7826368,0.005281267,0.001498671,0.004046388,0.0002111367],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4458763,0.0005360148,0.5429437,0.0003065291,0.0002573773,0.001503416,0.00242432,0.002240048,0.003912326],"genre_scores_gemma":[0.6919965,0.0001614887,0.3051146,0.00006835105,0.00007475218,0.0005860424,0.001251911,0.00008991767,0.0006565009],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00985898,"threshold_uncertainty_score":0.05213988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01480008498384669,"score_gpt":0.2613715016013514,"score_spread":0.2465714166175047,"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."}}