{"id":"W3159137602","doi":"10.3354/cr01657","title":"Backward trajectory analysis of southern California atmospheric rivers","year":2021,"lang":"en","type":"article","venue":"Climate Research","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Landfall; Climatology; Environmental science; Storm; Orographic lift; Forcing (mathematics); Atmospheric sciences; Atmosphere (unit); Meteorology; Geography; Geology; Precipitation","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009070513,0.00008268381,0.0001963778,0.00004239268,0.0001403111,0.00002887856,0.0002418429,0.00004126783,0.01816148],"category_scores_gemma":[0.00003062491,0.00007340246,0.0001419363,0.002058182,0.0002375586,0.00005065635,0.0005116107,0.0001452848,0.002744565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001603745,"about_ca_system_score_gemma":0.0000228807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005813847,"about_ca_topic_score_gemma":0.001123707,"domain_scores_codex":[0.9980984,0.0002125137,0.0001844298,0.0003147614,0.0007455525,0.0004443557],"domain_scores_gemma":[0.999378,0.00008262245,0.0000403389,0.0003668789,0.00003420829,0.00009795009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005251894,0.0004838999,0.9335036,0.000095868,0.0008307504,0.0001210801,0.00100056,0.01954142,0.01726169,0.0001844701,0.008865058,0.01805914],"study_design_scores_gemma":[0.001529188,0.0002834552,0.7166695,0.00005279402,0.001449694,0.000002200846,0.01861772,0.1100465,0.006712536,0.0006364714,0.1431942,0.0008057646],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9630848,0.0001114443,0.0002233912,0.000159412,0.00003322344,0.0001275654,0.0001069773,0.00002215767,0.03613105],"genre_scores_gemma":[0.9935704,0.0008622614,0.003239312,0.00003440859,0.00001627804,0.00001737077,0.00006536866,0.00001648979,0.002178142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.216834,"threshold_uncertainty_score":0.9980319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03460974490189075,"score_gpt":0.3273448374369808,"score_spread":0.2927350925350901,"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."}}