{"id":"W2562350296","doi":"10.1175/waf-d-16-0139.1","title":"Statistical Forecast Model for Ice-Related Events in the Arctic","year":2017,"lang":"en","type":"article","venue":"Weather and Forecasting","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Arctic; Climatology; Event (particle physics); Meteorology; The arctic; Environmental science; Statistical model; Forecast error; Filter (signal processing); Computer science; Econometrics; Geology; Mathematics; Geography; Oceanography; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001926288,0.0004440742,0.0006498902,0.0008809722,0.0003726731,0.0008887838,0.001168656,0.0007097161,0.002070377],"category_scores_gemma":[0.00464017,0.0003187155,0.000677394,0.0006850071,0.00050444,0.001173198,0.0003559727,0.000954876,0.0004748156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283393,"about_ca_system_score_gemma":0.001606217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0374381,"about_ca_topic_score_gemma":0.01927344,"domain_scores_codex":[0.9995081,0.0001215306,0.00002739809,0.0001163669,0.0001579845,0.00006854277],"domain_scores_gemma":[0.9979755,0.001154868,0.0003093832,0.00005761941,0.0004523723,0.00005024504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002454928,0.00001162216,0.001154922,0.000008220831,0.00001370754,0.00002232566,0.00001979442,0.9811731,0.0003714914,0.01207468,0.0003550683,0.004770495],"study_design_scores_gemma":[0.000001753498,0.000004127331,0.000129786,8.923136e-7,0.000002712677,0.000003122076,0.000002031961,0.9985372,0.00005631322,0.001172218,0.00008731741,0.000002429303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1200329,0.0001539206,0.8737009,0.0006626116,0.0001233625,0.00004251654,0.0008390639,0.0007615559,0.003683063],"genre_scores_gemma":[0.9576958,0.0002704886,0.03562155,0.00009179693,0.0001127185,0.0001466561,0.0009028594,0.00008089131,0.005077288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0374381,"threshold_uncertainty_score":0.07444036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04323587111202244,"score_gpt":0.2524154873670946,"score_spread":0.2091796162550721,"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."}}