{"id":"W2181244962","doi":"10.1175/jtech1956.1","title":"Sampling Errors in the Measurement of Rainfall Parameters Using the Precipitation Occurrence Sensor System (POSS)","year":2007,"lang":"en","type":"article","venue":"Journal of Atmospheric and Oceanic Technology","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Disdrometer; Precipitation; Environmental science; Radar; Sampling (signal processing); Quantitative precipitation estimation; Monte Carlo method; Meteorology; Statistics; Remote sensing; Computer science; Mathematics; Geology; Rain gauge","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":[],"consensus_categories":[],"category_scores_codex":[0.003286636,0.00009010416,0.0002049982,0.00004287366,0.00009968646,0.00002013753,0.0002676212,0.00006927354,0.00001079345],"category_scores_gemma":[0.0001987294,0.00004919343,0.00006600141,0.0006780611,0.0001234884,0.0001085737,0.000007016282,0.0002157961,6.881792e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002160311,"about_ca_system_score_gemma":0.00005235805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005506689,"about_ca_topic_score_gemma":0.0001920197,"domain_scores_codex":[0.9986585,0.00009223429,0.0005357841,0.00009645677,0.0004423575,0.0001746681],"domain_scores_gemma":[0.9989274,0.0002055076,0.0005440863,0.0001132834,0.0001818083,0.00002788823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002333602,0.00005289769,0.8605231,0.00009528766,0.0002094758,0.000027135,0.00426689,0.02968487,0.00173691,0.0003044761,0.00005396722,0.1028116],"study_design_scores_gemma":[0.001520243,0.0008222862,0.8331573,0.0005136965,0.0004567918,0.0004014296,0.09406624,0.06546631,0.0008986782,0.001567819,0.0007700623,0.000359133],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822755,0.001567789,0.01556042,0.0002718507,0.0001393575,0.000104139,0.000002386869,0.00000777831,0.00007075209],"genre_scores_gemma":[0.9870389,0.00006843176,0.01282777,0.00004152925,0.00002056542,1.331125e-7,5.159276e-7,0.000001380572,7.863919e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1024525,"threshold_uncertainty_score":0.200605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03973956952897922,"score_gpt":0.2546209901463792,"score_spread":0.2148814206174,"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."}}