{"id":"W7065667185","doi":"","title":"Evaluating conditional density estimation networks as a probabilistic
\\ndownscaling tool: application to precipitation in Newfoundland","year":2015,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Downscaling; Precipitation; Probabilistic logic; Extreme value theory; Estimation; Return period; Conditional probability distribution; Generalized extreme value distribution; Statistical model","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":[0.005050741,0.0006567987,0.0005188247,0.001160233,0.0004745556,0.001127995,0.00118423,0.0007157254,0.001719572],"category_scores_gemma":[0.01636431,0.000375635,0.000528321,0.0007577398,0.0005929314,0.0009319573,0.00107106,0.0008362461,0.0001288667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004412189,"about_ca_system_score_gemma":0.002374711,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4714189,"about_ca_topic_score_gemma":0.4262985,"domain_scores_codex":[0.9993967,0.0002981352,0.00003378843,0.000121799,0.0000818613,0.00006772685],"domain_scores_gemma":[0.9899907,0.007827543,0.0004251415,0.0003393039,0.001229837,0.0001875698],"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":[0.00008656112,0.00005706759,0.01553042,0.00003195787,0.0000650905,0.00005704767,0.00005603055,0.9509312,0.0002020807,0.001476492,0.000966087,0.03054001],"study_design_scores_gemma":[0.000004139718,0.000005275854,0.001148885,0.000003498548,0.000004145162,0.000002757705,0.00001339049,0.9983967,0.00009638155,0.0002498889,0.00007234509,0.000002570473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7358125,0.0007645246,0.2538392,0.001179719,0.00006659542,0.0002192793,0.001191992,0.001874629,0.005051585],"genre_scores_gemma":[0.9230492,0.0002178472,0.07392006,0.00009699169,0.00002477798,0.00007748605,0.001065384,0.00008648012,0.001461883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5285811,"threshold_uncertainty_score":0.9373499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02954436990945488,"score_gpt":0.3229626140771721,"score_spread":0.2934182441677173,"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."}}