{"id":"W2987943406","doi":"","title":"An Assessment of Two Statistical Downscaling Techniques for Generating Daily Climate Data for Central Canada","year":2007,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Downscaling; Climate change; Climatology; Environmental science; Geography; Computer science; Statistics; Meteorology; Precipitation; Mathematics; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004968066,0.0006635262,0.0004424293,0.001719688,0.001140822,0.00143057,0.00133779,0.0006644457,0.00132334],"category_scores_gemma":[0.01938603,0.0004560828,0.0008823238,0.002796003,0.0004199442,0.0009445412,0.000872639,0.0006557107,0.0002435967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003516446,"about_ca_system_score_gemma":0.006790566,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5336624,"about_ca_topic_score_gemma":0.6171315,"domain_scores_codex":[0.9985188,0.0003376344,0.0001223138,0.0001933798,0.0006823571,0.0001454957],"domain_scores_gemma":[0.9873093,0.00478599,0.0005515642,0.0008391779,0.006235001,0.0002790276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001924854,0.0004110883,0.08824353,0.0004675903,0.000627794,0.0001592776,0.001227933,0.2379255,0.0183384,0.004489565,0.006309178,0.6398754],"study_design_scores_gemma":[0.000370547,0.0002365501,0.09860797,0.0000550151,0.0003294387,0.00008008751,0.000564086,0.8815234,0.01145303,0.001141305,0.005518504,0.000120014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7604047,0.001121014,0.2219311,0.00144652,0.0001999795,0.0005559243,0.003126278,0.003336004,0.007878655],"genre_scores_gemma":[0.6318753,0.0005532992,0.3625015,0.000150365,0.00006688351,0.0002056455,0.002326422,0.0005300949,0.001790463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4663376,"threshold_uncertainty_score":0.9381679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03714351725868403,"score_gpt":0.3468049856592275,"score_spread":0.3096614684005435,"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."}}