{"id":"W4415269391","doi":"10.2139/ssrn.5616772","title":"Enhancing Accuracy of Numerical Weather Prediction Models in Road Surface Temperature Forecasting for Winter Road Maintenance Operations in Cold Climate Regions","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Numerical weather prediction; Road surface; Weather forecasting; Mean squared error; Predictive modelling; Standard deviation; Weather station","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":[0.0009178922,0.0005577743,0.0006090541,0.0003331596,0.0003397313,0.001128177,0.0006637773,0.0008802308,0.001203283],"category_scores_gemma":[0.004191285,0.0003491071,0.0005942389,0.0003780062,0.000204685,0.001065404,0.0004214586,0.0008902077,0.0004710603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004556479,"about_ca_system_score_gemma":0.0007097648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03527509,"about_ca_topic_score_gemma":0.01921006,"domain_scores_codex":[0.9997409,0.00006282788,0.00002259689,0.00008597846,0.00004913081,0.00003857072],"domain_scores_gemma":[0.99831,0.0008609264,0.0001162953,0.0002142989,0.0004249378,0.00007354304],"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":[0.0002657987,0.0002058817,0.0183406,0.00005248417,0.00006677729,0.000043127,0.00005057699,0.9339745,0.004895365,0.0002984904,0.0008734542,0.04093303],"study_design_scores_gemma":[0.000004416916,0.00001603795,0.001594422,0.000002153479,0.000007117796,0.000002196273,0.000007306617,0.9973986,0.0008381146,0.00006876305,0.00005750586,0.000003276522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9093182,0.0003864095,0.08410548,0.0005431197,0.0002359194,0.00003540056,0.0007063682,0.001207497,0.003461637],"genre_scores_gemma":[0.9932067,0.00005730892,0.005972399,0.00001950874,0.00002200227,0.000008404122,0.0002961589,0.00002746001,0.0003900121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03527509,"threshold_uncertainty_score":0.07013953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01312464497059412,"score_gpt":0.2456845479533726,"score_spread":0.2325599029827785,"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."}}