{"id":"W2949787734","doi":"10.1002/hyp.13534","title":"Implication of evaporative loss estimation methods in discharge and water temperature modelling in cool temperate climates","year":2019,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Geological Survey","keywords":"Evapotranspiration; Evaporation; Environmental science; Potential evaporation; Evaporative cooler; Hydrology (agriculture); Atmospheric sciences; Meteorology; Geology; Ecology; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005143175,0.0001253555,0.000229733,0.00005214092,0.00005010714,0.00001239059,0.00009659159,0.0001052179,0.0001610101],"category_scores_gemma":[0.00004442149,0.00007638564,0.00001260528,0.0002007313,0.0001797893,0.0003048446,0.0001582824,0.0001339858,0.0000470989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002164886,"about_ca_system_score_gemma":0.000002605801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004490416,"about_ca_topic_score_gemma":0.0000215782,"domain_scores_codex":[0.9990039,0.0001049863,0.0002615232,0.0003293041,0.00008326348,0.0002170363],"domain_scores_gemma":[0.99973,0.00008537906,0.00006043957,0.00009269749,0.00001013259,0.00002133773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001687198,0.0001561329,0.5767708,0.0002237933,0.00001102251,0.000002979158,0.002258284,0.3615811,0.05836068,0.0001931042,0.000008682418,0.0002646885],"study_design_scores_gemma":[0.002090337,0.0006163662,0.1867338,0.0001361787,0.00004369214,0.000009553803,0.0005560882,0.4995824,0.2497932,0.05948688,0.0001882621,0.0007631752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997151,0.00009960953,0.001227004,0.0006096025,0.00001374094,0.0003415445,0.000001868802,0.0000169621,0.0005387165],"genre_scores_gemma":[0.9968535,0.0001493907,0.002739451,0.0001187333,0.000003228815,0.00006077772,0.00001532515,0.000004907698,0.00005470399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3900369,"threshold_uncertainty_score":0.3114916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01778391276871942,"score_gpt":0.2919631284448413,"score_spread":0.2741792156761219,"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."}}