{"id":"W7071480695","doi":"","title":"Spatial Data Analysis for the Development of Expected Adverse Weather Charts for Transportation Construction Projects","year":2023,"lang":"en","type":"article","venue":"Open PRAIRIE (South Dakota State University)","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydrography; Interim; Climate change; Weather station; Weather forecasting; Extreme weather; Adverse weather; Geographic information 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":[],"consensus_categories":[],"category_scores_codex":[0.0004188632,0.0001095119,0.0002030174,0.0001729547,0.0004011339,0.00001581028,0.0007086607,0.00005142127,0.0003902858],"category_scores_gemma":[0.00002921203,0.00009349715,0.00008854989,0.001376211,0.0001759249,0.0004298821,0.0001839661,0.00004590692,0.00003349096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004999766,"about_ca_system_score_gemma":0.00007006567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004473962,"about_ca_topic_score_gemma":0.01571042,"domain_scores_codex":[0.9989761,0.00004983746,0.0002074561,0.0004180701,0.0001488678,0.000199734],"domain_scores_gemma":[0.9991906,0.0001152042,0.0002070824,0.0004119159,0.0000292636,0.00004591732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003402089,0.0002907654,0.843097,0.00007818068,0.00653473,0.00002821619,0.06512993,0.03664463,0.0009587613,0.0007766795,0.005608813,0.03745025],"study_design_scores_gemma":[0.00584065,0.0002427525,0.4800372,0.00002415456,0.005703887,7.389719e-7,0.02958109,0.089097,0.002075535,0.0003078214,0.3861998,0.0008893601],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5970398,0.000002398764,0.3979076,0.0004388982,0.00008795343,0.00170801,0.001356986,0.00005074449,0.00140757],"genre_scores_gemma":[0.9787211,0.000004880729,0.01399334,0.00002028306,0.000009807,0.00001728233,0.001828366,0.00001086848,0.005394039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3839143,"threshold_uncertainty_score":0.8766782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04674091585841393,"score_gpt":0.2580295692970399,"score_spread":0.211288653438626,"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."}}