{"id":"W2321925644","doi":"10.1061/9780784413548.064","title":"Multisite Statistical Downscaling of Daily Precipitation Processes","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Downscaling; Precipitation; Climatology; Environmental science; Climate change; Singular value decomposition; Meteorology; Computer science; Geography; Geology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002739354,0.000163385,0.0001992038,0.00003862282,0.0001236133,0.00003330148,0.0001337138,0.00004625898,0.002410373],"category_scores_gemma":[0.00001594869,0.0001175223,0.00002793845,0.00003573951,0.0005350579,0.0001768925,0.0002554554,0.00008590708,0.0002730076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003069135,"about_ca_system_score_gemma":5.58073e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002320722,"about_ca_topic_score_gemma":0.000217793,"domain_scores_codex":[0.9987459,0.0000906885,0.0002829788,0.0003649181,0.0002549575,0.0002605332],"domain_scores_gemma":[0.9994805,0.0001403391,0.00006973524,0.0001914586,0.000002097107,0.0001158365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001985124,0.0003544971,0.8815214,0.000259755,0.00003412934,0.000003315996,0.006124149,0.006058292,0.08455639,0.0001376499,0.0006512109,0.02010071],"study_design_scores_gemma":[0.003321045,0.0005562399,0.5794158,0.0001728042,0.0001998861,0.0000248729,0.0005230727,0.04371236,0.08722806,0.006725527,0.2766546,0.00146573],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961213,0.00004609952,0.001007273,0.0001022709,0.00005621148,0.000176075,0.00004732705,0.00002255317,0.002420895],"genre_scores_gemma":[0.9974055,0.00004213092,0.001257627,0.0000928397,0.00002667147,0.0000172832,0.00005752355,0.00001507424,0.001085386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3021056,"threshold_uncertainty_score":0.9985015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007050167844099076,"score_gpt":0.2025483988207188,"score_spread":0.1954982309766198,"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."}}