{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001961569,0.000485947,0.0003053076,0.0006136093,0.0004036283,0.0009621346,0.0006624442,0.0005106652,0.0004945842],"category_scores_gemma":[0.005538465,0.0003385068,0.0004902509,0.0006292828,0.0003258258,0.0006974353,0.0003948452,0.0006189927,0.0001258261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001030956,"about_ca_system_score_gemma":0.001142728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07758587,"about_ca_topic_score_gemma":0.1509089,"domain_scores_codex":[0.9994011,0.0001613372,0.00007063238,0.0002141651,0.0001095594,0.00004316098],"domain_scores_gemma":[0.9964605,0.001928741,0.0004503565,0.0003818526,0.0005678459,0.0002108215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00150232,0.002282484,0.5529879,0.000367293,0.00100335,0.0003958608,0.0008084506,0.3410642,0.008025119,0.0006846318,0.01268612,0.07819224],"study_design_scores_gemma":[0.0003305558,0.00077223,0.4462321,0.000068657,0.000311032,0.00003792514,0.0009616347,0.5401907,0.006252546,0.0005584269,0.004180404,0.0001038062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935265,0.0001016536,0.0009854164,0.0001174885,0.00004261358,0.00007500638,0.003118765,0.0002238088,0.001808832],"genre_scores_gemma":[0.9904844,0.00007343027,0.003145863,0.00004311744,0.00002913882,0.00006653145,0.005931157,0.00001961459,0.000206716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07758587,"threshold_uncertainty_score":0.1542686,"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."}}