{"id":"W3093597938","doi":"10.1109/tgrs.2020.3028525","title":"Characterization of the Systematic and Random Errors in Satellite Precipitation Using the Multiplicative Error Model","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Global Water Futures; National Natural Science Foundation of China","keywords":"Precipitation; Multiplicative function; Random error; Systematic error; Environmental science; Satellite; Computer science; Statistics; Climatology; Meteorology; Algorithm; Mathematics; Geology; Physics","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":[0.002611979,0.000795213,0.0004497157,0.00153183,0.0002823303,0.0007559994,0.001041301,0.0005809864,0.00046493],"category_scores_gemma":[0.008379193,0.0002703624,0.0009096708,0.00112276,0.0005029416,0.001395295,0.001163912,0.0005371783,0.0001233296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003888074,"about_ca_system_score_gemma":0.0008371936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004877042,"about_ca_topic_score_gemma":0.003983893,"domain_scores_codex":[0.9984156,0.0003947876,0.0001253424,0.0003081322,0.0006273266,0.0001287595],"domain_scores_gemma":[0.9969819,0.001560275,0.0004407473,0.0002866624,0.0006662337,0.00006416796],"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":[0.0002002694,0.0001090697,0.07180052,0.0002255999,0.0003415334,0.0002835849,0.0003127023,0.7928749,0.0140414,0.0261525,0.001027958,0.09263001],"study_design_scores_gemma":[0.0000101903,0.00004817537,0.01103963,0.00001192733,0.0000544096,0.00009139429,0.00003540102,0.9821894,0.00224444,0.003583866,0.0006638708,0.00002734327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2305452,0.0004459081,0.7661076,0.0002141405,0.00007942271,0.00007947552,0.0002288488,0.0002593446,0.002040038],"genre_scores_gemma":[0.9460437,0.0003019617,0.05195929,0.00005560267,0.00006200153,0.00008131206,0.0003885144,0.00005458065,0.001052965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004877042,"threshold_uncertainty_score":0.01381361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04191375978821883,"score_gpt":0.2398571752662786,"score_spread":0.1979434154780598,"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."}}