{"id":"W2853563898","doi":"10.1002/hyp.13226","title":"The importance of incorporating diurnally fluctuating stream discharge in stream temperature energy balance models","year":2018,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Division of Earth Sciences; Division of Graduate Education; National Science Foundation","keywords":"Streamflow; Environmental science; Discharge; Evapotranspiration; Hydrology (agriculture); Snow; Estuary; Inflow; Energy balance; Groundwater; Atmospheric sciences; Geology; Meteorology; Geomorphology; Physics; Geography; Ecology; Drainage basin","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0009479491,0.0004892736,0.0004337561,0.0002287534,0.0004247382,0.001018129,0.0007566945,0.000871864,0.0005499594],"category_scores_gemma":[0.004975461,0.0003648374,0.0005523554,0.000279937,0.0004042173,0.001118569,0.0005428076,0.0008001873,0.000089299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005162213,"about_ca_system_score_gemma":0.0009597564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02511537,"about_ca_topic_score_gemma":0.02146292,"domain_scores_codex":[0.9995487,0.0002346048,0.00003802395,0.00008558704,0.00005428044,0.00003869615],"domain_scores_gemma":[0.9984621,0.0009747053,0.0001498606,0.0001568723,0.0001961415,0.00006035429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003071039,0.00005390365,0.01243724,0.00001911142,0.00004857655,0.00003804263,0.00003067339,0.9805195,0.002057112,0.0004092239,0.0001242624,0.00423163],"study_design_scores_gemma":[0.000006188847,0.00001698051,0.001924286,0.000004068084,0.000007955524,0.000005826028,0.0000104656,0.9973047,0.0004292117,0.0001715046,0.0001120126,0.000006819675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9369321,0.0002958522,0.05838642,0.0006461277,0.00007243813,0.00004211548,0.0003364758,0.0003819827,0.002906386],"genre_scores_gemma":[0.9964946,0.00004405879,0.003163612,0.00003464853,0.000008881005,0.00001137654,0.00008165037,0.00001933451,0.000141877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02511537,"threshold_uncertainty_score":0.04993838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081272477984935,"score_gpt":0.2211793743196654,"score_spread":0.210366649539816,"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."}}