{"id":"W4387079181","doi":"10.1016/j.jhydrol.2023.130246","title":"Macroscale composite principal-monotonicity distributed projection of climate-induced hydrologic changes: Tempo-spatial variabilities, and variation decompositions","year":2023,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Resources Canada; Environment and Climate Change Canada; Western Economic Diversification Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Environmental science; Greenhouse gas; Spatial variability; Climate change; Dominance (genetics); Watershed; Spatial ecology; Atmospheric sciences; Hydrology (agriculture); Drainage basin; Climatology; Physical geography; Geology; Geography; Statistics; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007519381,0.0003197043,0.000238478,0.001542157,0.0002478475,0.0008526011,0.0002359607,0.0001688148,0.002498641],"category_scores_gemma":[0.002316578,0.0001819425,0.000478716,0.001139991,0.0002323793,0.0005755896,0.0004168067,0.0003436822,0.0002755278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003191738,"about_ca_system_score_gemma":0.0005061388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003952221,"about_ca_topic_score_gemma":0.005124803,"domain_scores_codex":[0.9998212,0.00003702871,0.00001012381,0.00005238655,0.0000496721,0.0000294791],"domain_scores_gemma":[0.9989183,0.0003103404,0.0001513403,0.0001355388,0.0003830022,0.0001015398],"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":[0.001028124,0.0004054481,0.282447,0.000131192,0.0003560852,0.0003478068,0.0004323833,0.3587814,0.03895,0.02369961,0.003640076,0.2897808],"study_design_scores_gemma":[0.00001045699,0.00005111414,0.2619401,0.000006973822,0.00003096323,0.00007461181,0.00009349328,0.7314631,0.001409786,0.004092794,0.0007978076,0.00002879915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.88352,0.00006629088,0.1111174,0.00008445009,0.00002145203,0.00004283847,0.001755748,0.0003659379,0.003025946],"genre_scores_gemma":[0.9809584,0.00005581299,0.01702485,0.00000829181,0.00001805328,0.00002628228,0.001029211,0.00007330667,0.0008058234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003952221,"threshold_uncertainty_score":0.008358717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0128171041628154,"score_gpt":0.2508586159674201,"score_spread":0.2380415118046047,"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."}}