{"id":"W2914221007","doi":"10.1016/j.jenvrad.2019.01.009","title":"Large area decontamination after a radiological incident","year":2019,"lang":"en","type":"article","venue":"Journal of Environmental Radioactivity","topic":"Nuclear and radioactivity studies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Canadian Nuclear Laboratories","funders":"Canadian Nuclear Laboratories; Environment and Climate Change Canada; U.S. Department of Homeland Security; U.S. Environmental Protection Agency","keywords":"Human decontamination; Contamination; Environmental science; Asphalt; Radiological weapon; Waste management; Environmental engineering; Materials science; Engineering; Radiochemistry; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002409705,0.0003042702,0.0004010641,0.0007799693,0.001144097,0.0005319917,0.0004122538,0.0009883831,0.003062598],"category_scores_gemma":[0.0009604056,0.000167052,0.0003542138,0.00039831,0.0004946037,0.0003468713,0.0005042761,0.0006749272,0.0005371082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002974649,"about_ca_system_score_gemma":0.0004143213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002704345,"about_ca_topic_score_gemma":0.004281921,"domain_scores_codex":[0.9998187,0.00003948433,0.000009513737,0.00002300892,0.00005952497,0.00004979311],"domain_scores_gemma":[0.9996492,0.0001096459,0.00005088737,0.0000421619,0.0001102408,0.00003791599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02165241,0.003877783,0.1081889,0.0005315337,0.0001648874,0.08864444,0.008132799,0.00497797,0.54501,0.001067797,0.002693508,0.2150581],"study_design_scores_gemma":[0.0004247553,0.0421947,0.4287714,0.0001753249,0.0004470466,0.05528717,0.01358067,0.006615757,0.419767,0.001929615,0.03064368,0.0001628536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938234,0.0003578905,0.001306268,0.0001673168,0.0000545995,0.00006452663,0.00003335169,0.0000607344,0.004132013],"genre_scores_gemma":[0.9968822,0.0001089017,0.0003344757,0.00009568177,0.00001350205,0.000006861189,0.00003063603,0.0000143644,0.002513399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003062598,"threshold_uncertainty_score":0.01024544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003839357724977923,"score_gpt":0.1794762667812043,"score_spread":0.1756369090562263,"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."}}