{"id":"W2069018481","doi":"10.1002/met.175","title":"A seasonal forecast scheme for spring dust storm predictions in Northern China","year":2010,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Natural Science Foundation of China","keywords":"Climatology; Storm; Dust storm; Environmental science; Empirical orthogonal functions; Precipitation; Meteorology; Forecast skill; Geography; Geology","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":[],"category_scores_codex":[0.0001888042,0.0001148801,0.000120597,0.000002076382,0.0002335815,0.00001767518,0.0002593385,0.0001230758,0.001064849],"category_scores_gemma":[0.00004182953,0.00009327572,0.00007151144,0.0002486788,0.0001926518,0.00007081183,0.0001210167,0.0002684537,0.0001730031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006134179,"about_ca_system_score_gemma":0.000009773624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001915398,"about_ca_topic_score_gemma":0.007428354,"domain_scores_codex":[0.9990569,0.00001120779,0.0001801781,0.000337415,0.000135072,0.0002792674],"domain_scores_gemma":[0.9995127,0.00005999302,0.00005531816,0.0002463221,0.000008328583,0.0001173173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001651067,0.0002841122,0.9596366,0.00000279988,0.000006404739,5.254238e-7,0.00005185774,0.0005624466,0.01145358,0.0052894,0.0001615237,0.02253427],"study_design_scores_gemma":[0.0002571794,0.00006277602,0.90803,9.489061e-7,0.000008861773,0.000003412094,0.00002235364,0.01181527,0.00007977965,0.002927932,0.07666085,0.000130619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9138708,0.00001010311,0.08066679,0.0007130383,0.00004055829,0.0006649729,0.00001920569,0.00007292483,0.003941625],"genre_scores_gemma":[0.9542053,0.000002330545,0.04338742,0.0001143693,0.00009834198,0.001947143,0.00001130741,0.00001111796,0.0002226572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07649933,"threshold_uncertainty_score":0.9998483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01057439401642717,"score_gpt":0.2295932179303747,"score_spread":0.2190188239139475,"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."}}