{"id":"W2328294207","doi":"10.1097/hp.0000000000000365","title":"The Sensitivity of Atmospheric Dispersion Calculations in Near-field Applications","year":2016,"lang":"en","type":"article","venue":"Health Physics","topic":"Nuclear and radioactivity studies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nuclear Laboratories; Environment and Climate Change Canada; Defence Research and Development Canada","funders":"","keywords":"Atmospheric dispersion modeling; Environmental science; Sensitivity (control systems); Dispersion (optics); Ground level; Deposition (geology); Scale (ratio); Field (mathematics); Meteorology; Atmospheric sciences; Nuclear engineering; Remote sensing; Physics; Optics; Geology; Air pollution; Engineering; Chemistry; Mathematics; Geomorphology; Civil engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001610717,0.0006073861,0.0003892571,0.0006873263,0.0006476312,0.001141913,0.0009170666,0.001088698,0.0009722156],"category_scores_gemma":[0.006065735,0.0003211777,0.0005089646,0.0006069538,0.0003322408,0.0010661,0.0006716314,0.0006323216,0.0002727258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001303232,"about_ca_system_score_gemma":0.0008704835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0876264,"about_ca_topic_score_gemma":0.05267644,"domain_scores_codex":[0.9993911,0.0001968357,0.00003625593,0.0001930209,0.0001293602,0.00005343154],"domain_scores_gemma":[0.9969122,0.002176995,0.0001586893,0.0003179024,0.0003637085,0.0000705221],"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":[0.0001708446,0.0001058993,0.03105883,0.00004861136,0.0000791991,0.00006008842,0.00007858486,0.9450424,0.003478991,0.0007729852,0.000660724,0.01844285],"study_design_scores_gemma":[0.00003455612,0.00007307811,0.009935135,0.00001961121,0.00001801258,0.00003862664,0.00009756119,0.9845175,0.003435169,0.0006668096,0.001137168,0.00002679534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9677501,0.0004769268,0.02215862,0.0003929123,0.00006124735,0.00006979075,0.001209859,0.001120259,0.006760263],"genre_scores_gemma":[0.99042,0.00012348,0.008100851,0.0000482462,0.0000153758,0.00001437972,0.0006272365,0.00006210942,0.0005883002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0876264,"threshold_uncertainty_score":0.1742327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009724489473583512,"score_gpt":0.2530933727706379,"score_spread":0.2433688832970544,"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."}}