{"id":"W6977507907","doi":"10.6084/m9.figshare.25749171.v1","title":"Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Current Result","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"National weather service; Weather forecasting; Current (fluid); Weather prediction; Numerical weather prediction; Tropical cyclone forecast model; Global Forecast System","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00005384899,0.0004281602,0.0003509302,0.0002919369,0.00008476254,0.0001120016,0.0004437137,0.0004443048,0.03384988],"category_scores_gemma":[0.00009101977,0.0004045343,0.0002843147,0.0003234879,0.00001214584,0.0002273644,0.0001330739,0.001064214,0.003961638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002832066,"about_ca_system_score_gemma":0.0001309948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000561986,"about_ca_topic_score_gemma":0.0000430504,"domain_scores_codex":[0.9984131,0.00002116821,0.0003303116,0.0004837647,0.0003811842,0.0003704945],"domain_scores_gemma":[0.9990653,0.00003097876,0.00005474748,0.0006379217,0.00009162733,0.0001194724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003152347,0.000005723395,3.128018e-8,0.0006585376,0.00005028002,0.000003878598,0.00002117146,0.4636779,9.953986e-7,9.332758e-7,0.5340274,0.001550001],"study_design_scores_gemma":[0.00004904759,0.000007467906,3.349321e-7,0.0007392852,0.0000900871,0.000001731286,0.000006005752,0.5074161,0.0000075361,0.0001009787,0.4913961,0.0001853169],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002045997,0.0013801,0.0002654401,0.00001100626,0.0002660311,0.0002145017,0.9969525,0.0002930382,0.0006153072],"genre_scores_gemma":[0.0002031841,0.0002796013,0.00005651873,0.00001518765,0.0004083008,0.0001036498,0.9987655,0.00005304047,0.0001150413],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04373826,"threshold_uncertainty_score":0.9998407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02222574015274238,"score_gpt":0.2426606603526629,"score_spread":0.2204349201999206,"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."}}