{"id":"W2020960189","doi":"10.4296/cwrj3004297","title":"An Application of the Statistical DownScaling Model (SDSM) to Simulate Climatic Data for Streamflow Modelling in Québec","year":2005,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Downscaling; Streamflow; Climatology; Environmental science; Precipitation; General Circulation Model; Climate model; Climate change; Scale (ratio); Meteorology; Drainage basin; Geography; Geology; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001015087,0.0002363304,0.0003264792,0.0002287803,0.0006485003,0.0000852849,0.001308471,0.00009874285,0.00004529611],"category_scores_gemma":[0.00008208593,0.0001680601,0.00006293317,0.0001770426,0.0003427452,0.0003799131,0.0001930133,0.0002615036,0.00001154162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008201448,"about_ca_system_score_gemma":0.000008248578,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3624572,"about_ca_topic_score_gemma":0.9655676,"domain_scores_codex":[0.9977252,0.0001449803,0.0005985386,0.0004930816,0.0001337515,0.0009044712],"domain_scores_gemma":[0.9983656,0.00008181783,0.0001407254,0.0007397013,0.00003476135,0.0006373437],"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":[0.00004022054,0.00002238346,0.009122676,0.0000396242,0.00002617393,0.000008942126,0.09051185,0.894032,0.000320267,0.000005232906,0.00002417303,0.005846454],"study_design_scores_gemma":[0.0002208077,0.00007325532,0.000683206,0.00006789382,0.00004816649,0.00001671285,0.0002834191,0.9030033,0.0002416183,0.001631645,0.09350356,0.000226393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719776,0.00007986149,0.02481409,0.002203851,0.00003196083,0.000502698,0.0001649573,0.00001416986,0.0002108319],"genre_scores_gemma":[0.9927904,0.0000272366,0.006269198,0.0005573026,0.0001032987,0.0000348764,0.00004054848,0.00003504394,0.0001420996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6031104,"threshold_uncertainty_score":0.6853294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02386308112910012,"score_gpt":0.2416032864042193,"score_spread":0.2177402052751192,"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."}}