{"id":"W4371783470","doi":"10.2139/ssrn.4437064","title":"Towards Replacing Precipitation Ensemble Predictions Systems Using Machine Learning","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Ensemble learning; Precipitation; Computer science; Artificial intelligence; Machine learning; Meteorology; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003043949,0.0007691119,0.001080126,0.0006923645,0.0004300616,0.001859041,0.001674508,0.001249215,0.003526222],"category_scores_gemma":[0.00982292,0.0005897858,0.0006705617,0.0009882207,0.0004969731,0.003605216,0.001825853,0.002182758,0.001777717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004777019,"about_ca_system_score_gemma":0.001087872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007230991,"about_ca_topic_score_gemma":0.005315499,"domain_scores_codex":[0.9989542,0.0004031701,0.00008758286,0.0002711893,0.0002138998,0.00006999748],"domain_scores_gemma":[0.9959864,0.001291862,0.0002512496,0.001340475,0.001034232,0.00009578123],"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":[0.0003644172,0.0002587872,0.005948754,0.0001575582,0.0004615986,0.00009804522,0.0001096475,0.6334359,0.006405934,0.01292369,0.00710048,0.3327353],"study_design_scores_gemma":[0.00001151214,0.0000183247,0.0002810661,0.000007042736,0.00002188593,0.000008094043,0.00000707997,0.9913367,0.001319737,0.005384827,0.001597301,0.000006334828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05455522,0.000649029,0.9339563,0.0009073726,0.0008481321,0.00007034424,0.000577997,0.004694937,0.003740657],"genre_scores_gemma":[0.6758935,0.0004681584,0.3160812,0.0004923362,0.0006066656,0.0001105713,0.001494272,0.000511646,0.004341739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007230991,"threshold_uncertainty_score":0.01609814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04638477343861751,"score_gpt":0.2664806001023494,"score_spread":0.2200958266637319,"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."}}