{"id":"W1526765446","doi":"","title":"Analysis of spatial uncertainty in LiDAR-derived building data and uncertainty propagation in modeling of urban atmospheric dispersion","year":2009,"lang":"en","type":"article","venue":"SHAREOK (University of Oklahoma; Oklahoma State University; Central Oklahoma University)","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Defense Threat Reduction Agency; McMaster University; National Aeronautics and Space Administration; U.S. Department of Energy","keywords":"Atmospheric dispersion modeling; Environmental science; Dispersion (optics); Lidar; Uncertainty analysis; Propagation of uncertainty; Meteorology; Atmospheric sciences; Remote sensing; Geography; Statistics; Mathematics; Geology; Air pollution; Optics; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003058024,0.0003671602,0.000855295,0.0007551783,0.0002769015,0.00001879522,0.00117951,0.0002075519,0.0002207539],"category_scores_gemma":[0.0000388468,0.0004956702,0.0002459977,0.004184241,0.0005773461,0.001010755,0.0008170256,0.0003254824,0.000003122982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009668225,"about_ca_system_score_gemma":0.0001583524,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03083348,"about_ca_topic_score_gemma":0.02339156,"domain_scores_codex":[0.9971201,0.0002572188,0.0004232581,0.001037294,0.0005371615,0.0006249826],"domain_scores_gemma":[0.9980932,0.0001201684,0.0005485823,0.0008505794,0.0001099722,0.0002774562],"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":[0.002595583,0.001130102,0.2827462,0.0001276566,0.0005278139,0.0004783759,0.01091106,0.6401637,0.02019876,0.000805076,0.00008941649,0.04022626],"study_design_scores_gemma":[0.002268183,0.0001854878,0.3317127,0.0001390625,0.0004984002,0.000003272715,0.008447712,0.655194,0.0001303875,0.00006055468,0.0009296888,0.0004306253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854149,0.00003419158,0.01143244,0.0001990039,0.000034067,0.0004990381,0.000419022,0.00004842829,0.001918943],"genre_scores_gemma":[0.9964874,0.0002812961,0.00254342,0.000008993877,0.000007380671,1.528545e-8,0.0003366032,0.00001420555,0.0003207357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04896648,"threshold_uncertainty_score":0.9997495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049947846735206,"score_gpt":0.1904583732580516,"score_spread":0.1799588947906996,"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."}}