{"id":"W7098891236","doi":"","title":"2009: The diurnal cycle of precipitation from Continental radar images and Numerical Weather Prediction Models. Part I: Methodology and seasonal comparison. Monthly Weather Review (in review","year":2013,"lang":"en","type":"article","venue":"","topic":"Phytochemistry and Biological Activities","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Precipitation; Diurnal cycle; Quantitative precipitation estimation; Quantitative precipitation forecast; Numerical weather prediction; Radar","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003739111,0.0001236616,0.0003688147,0.000002524719,0.0000592525,0.00001772619,0.00009976293,0.00006596842,0.001006038],"category_scores_gemma":[0.00008943543,0.00003741875,0.00005948064,0.00008164121,0.0001510013,0.0001752262,0.00005573419,0.0001239358,0.000002497398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006021629,"about_ca_system_score_gemma":0.000002764349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004997044,"about_ca_topic_score_gemma":0.00002280208,"domain_scores_codex":[0.9988604,0.0003512716,0.0003067736,0.0002259415,0.0001160742,0.0001395925],"domain_scores_gemma":[0.9991912,0.0005425587,0.0001308667,0.00004067158,0.00004118232,0.00005353743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002056287,0.0008242197,0.1010755,0.0009072677,0.0001513954,0.000002168659,0.0002133099,0.00001391029,0.3422523,0.0002922543,0.04491096,0.509151],"study_design_scores_gemma":[0.0006105911,0.0006840366,0.9465621,0.004074795,0.0001893947,0.00002425219,0.0007566113,0.004769092,0.01029129,0.01690453,0.01460959,0.0005237212],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8173205,0.17239,0.00008331623,0.007705695,0.00003427248,0.0006174816,0.0002013848,0.00002424525,0.001623104],"genre_scores_gemma":[0.9585009,0.03965035,0.0006442174,0.0008338042,0.00009263739,0.00007239472,0.00006982308,8.065101e-7,0.0001350989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8454866,"threshold_uncertainty_score":0.9999072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04808131319191234,"score_gpt":0.2629243058063793,"score_spread":0.214842992614467,"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."}}