{"id":"W3207287378","doi":"10.17605/osf.io/upfxj","title":"Weather files-building simulations","year":2019,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Meteorology; Computer science; Environmental science; Geography","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":[0.0008774478,0.001905567,0.0009993917,0.001447115,0.0009749983,0.001580509,0.004078659,0.001368062,0.1490846],"category_scores_gemma":[0.003697132,0.0014536,0.001345856,0.002674388,0.0003798878,0.001837734,0.0009804938,0.001864096,0.04653331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001879042,"about_ca_system_score_gemma":0.002979398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1704,"about_ca_topic_score_gemma":0.2434255,"domain_scores_codex":[0.9994389,0.00005547574,0.00004562004,0.00008148116,0.0002638494,0.0001145528],"domain_scores_gemma":[0.9979391,0.00041883,0.00006550675,0.0004745031,0.0009276118,0.0001744874],"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":[0.0003421976,0.0001881799,0.003619081,0.000497898,0.000116941,0.0001547706,0.0002447256,0.05676216,0.002175234,0.004333243,0.9065028,0.02506266],"study_design_scores_gemma":[0.001611334,0.00005922802,0.008940659,0.0001774295,0.0001135265,0.0001325739,0.0002765787,0.2305747,0.01638839,0.00820524,0.733283,0.0002372956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.008353189,0.00008336571,0.02099722,0.0002556166,0.000260679,0.0003336057,0.8259321,0.1108174,0.03296689],"genre_scores_gemma":[0.04411554,0.0002957589,0.03668166,0.0002410548,0.00006624425,0.0008475044,0.8625589,0.03911626,0.01607708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1704,"threshold_uncertainty_score":0.4987378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01043263676519154,"score_gpt":0.2406047522822867,"score_spread":0.2301721155170952,"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."}}