{"id":"W7132058287","doi":"","title":"Road weather forecasting – ICEWARN model","year":2017,"lang":"en","type":"article","venue":"ASEP","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydrometeorology; Probabilistic logic; Parametrization (atmospheric modeling); Numerical weather prediction; Weather forecasting; Model output statistics; Tropical cyclone forecast model; Ensemble forecasting; Road surface","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004501461,0.0007472574,0.0009075445,0.0004194199,0.0004263389,0.0009273987,0.001830382,0.0009785211,0.00326828],"category_scores_gemma":[0.001094539,0.0004210349,0.0009860049,0.0006772578,0.0002911882,0.001356419,0.0007798029,0.001432275,0.001053321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009363952,"about_ca_system_score_gemma":0.001309877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05956255,"about_ca_topic_score_gemma":0.03090933,"domain_scores_codex":[0.9996294,0.00005526461,0.00002254994,0.0001307472,0.0001004614,0.00006156998],"domain_scores_gemma":[0.9996101,0.00006954159,0.00003928235,0.00006886887,0.0001721199,0.00004015216],"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":[0.00001451801,0.0000151426,0.001029764,0.00001221777,0.00001565398,0.0000186512,0.000005879302,0.9928377,0.0002745886,0.0006415241,0.001355052,0.003779259],"study_design_scores_gemma":[0.000005479527,0.000005126894,0.0003525288,0.00000180897,0.000005073561,0.000004125284,0.000001640342,0.9978535,0.0001780295,0.000255801,0.001331687,0.000005150898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2597399,0.0009138089,0.6520446,0.001432994,0.001267133,0.000310214,0.02803646,0.0064251,0.04982985],"genre_scores_gemma":[0.9011279,0.000438501,0.06657874,0.0001734498,0.0002542105,0.0002857086,0.01822481,0.0003685052,0.01254821],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05956255,"threshold_uncertainty_score":0.1184317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03045070623978009,"score_gpt":0.2399105234623739,"score_spread":0.2094598172225939,"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."}}