{"id":"W4387879914","doi":"10.1175/bams-d-22-0208.1","title":"From California’s Extreme Drought to Major Flooding: Evaluating and Synthesizing Experimental Seasonal and Subseasonal Forecasts of Landfalling Atmospheric Rivers and Extreme Precipitation during Winter 2022/23","year":2023,"lang":"en","type":"article","venue":"Bulletin of the American Meteorological Society","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Environment and Climate Change Canada; Jet Propulsion Laboratory; Nuclear Safety and Security Commission; California Institute of Technology; National Aeronautics and Space Administration; Department of Water Resources; National Science Foundation","keywords":"Environmental science; Climatology; Precipitation; Context (archaeology); Atmospheric research; Flooding (psychology); Meteorology; Geography; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006128289,0.0001775354,0.0003701349,0.00001009387,0.0002640049,0.00003151908,0.0001663149,0.00005936616,0.0007538334],"category_scores_gemma":[0.0003465145,0.0001187541,0.0001239115,0.000257986,0.000478946,0.00003578495,0.0001462674,0.000136888,0.00001005696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009925384,"about_ca_system_score_gemma":0.00001007255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000369907,"about_ca_topic_score_gemma":0.00001989541,"domain_scores_codex":[0.9983613,0.000278227,0.0003037885,0.0004064832,0.0003508979,0.0002993036],"domain_scores_gemma":[0.9983422,0.001107672,0.0002328116,0.0001227664,0.00003714684,0.0001574193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005889062,0.00004658076,0.9391279,0.00004399896,0.0001665241,0.000003225999,0.001785136,0.00551554,0.03313304,0.00001698898,0.0003994942,0.0191727],"study_design_scores_gemma":[0.0004830308,0.0003983198,0.9364597,0.00003556406,0.00006180037,0.000003131987,0.001750674,0.05929511,0.0005527575,0.0006058491,0.0001740639,0.0001800265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977774,0.0008298437,0.00009897062,0.0007856182,0.00005085933,0.0002437814,0.0001211826,0.000030545,0.00006182217],"genre_scores_gemma":[0.9774652,0.00008211028,0.02206249,0.0002315388,0.00007251972,0.000006536921,0.00002015206,0.000005899331,0.00005361756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05377956,"threshold_uncertainty_score":0.8253947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04191683407234568,"score_gpt":0.2538476117690885,"score_spread":0.2119307776967428,"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."}}