{"id":"W4244923741","doi":"10.5194/hess-2020-554","title":"Unshielded Precipitation Gauge Collection Efficiency with Wind Speed and Hydrometeor Fall Velocity. Part II: Experimental Results","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Exxon Mobil Corporation","keywords":"Wind speed; Precipitation; Environmental science; Mean squared error; Meteorology; Fence (mathematics); Gauge (firearms); Atmospheric sciences; Physics; Mathematics; Materials science; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004819462,0.0003333275,0.0003875743,0.0002411155,0.0004190223,0.0002289504,0.0002129764,0.0001848577,0.0008078401],"category_scores_gemma":[0.0001225234,0.0002685081,0.00009392589,0.0005202886,0.0001043574,0.0002202386,0.00006419019,0.0003299086,0.00005538157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002107656,"about_ca_system_score_gemma":0.00013555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00192984,"about_ca_topic_score_gemma":0.002742554,"domain_scores_codex":[0.9975713,0.0001799391,0.0004785345,0.0008081221,0.0006847286,0.0002773224],"domain_scores_gemma":[0.9990255,0.0001227101,0.000299165,0.0002296678,0.0001048309,0.0002181125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01737087,0.002225976,0.4907609,0.00164447,0.004920674,0.0002003593,0.1053462,0.2349309,0.01408636,0.000630967,0.08767686,0.04020546],"study_design_scores_gemma":[0.009685445,0.006698675,0.5004792,0.0007504555,0.001099873,0.00002676785,0.007637513,0.4408527,0.02154015,0.00272836,0.004722947,0.003777909],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800804,0.0003300951,0.0002671121,0.0008134058,0.000458346,0.0006004729,0.0001556966,0.0001261115,0.0171684],"genre_scores_gemma":[0.9942495,0.00007825834,0.001881471,0.0001370103,0.0001608249,0.000002230654,0.001464733,0.000007897852,0.002018089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2059218,"threshold_uncertainty_score":0.9999767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03803533175855721,"score_gpt":0.2382681940104135,"score_spread":0.2002328622518563,"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."}}