{"id":"W4395082757","doi":"10.1080/07370652.2024.2346327","title":"Database of in-plume emission factors from open demilitarization of military ordnance","year":2024,"lang":"en","type":"article","venue":"Journal of Energetic Materials","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Strategic Environmental Research and Development Program; Ames Research Center; University of Dayton; Office of Research and Development; U.S. Department of Defense; U.S. Environmental Protection Agency; Ministère de la Défense Nationale; National Aeronautics and Space Administration","keywords":"Explosive material; Detonation; Sampling (signal processing); Environmental science; Database; Unexploded ordnance; Plume; Particulates; Pollutant; Computer science; Meteorology; Archaeology; Remote sensing; Geology; Chemistry; Geography","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0008359568,0.001091031,0.001010218,0.01050925,0.0004167353,0.0009916348,0.0009479893,0.0004478061,0.005207379],"category_scores_gemma":[0.002051147,0.0003277555,0.0008276855,0.009598417,0.0001187666,0.0009154171,0.000498837,0.0003585098,0.002268786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008844623,"about_ca_system_score_gemma":0.001674161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03672657,"about_ca_topic_score_gemma":0.06116221,"domain_scores_codex":[0.9991986,0.00006681001,0.0001352899,0.0001869891,0.0003464493,0.00006581323],"domain_scores_gemma":[0.9970892,0.0008031607,0.0005695474,0.0002664539,0.001127492,0.0001441418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002094541,0.000947972,0.3621717,0.009799592,0.001723312,0.001667347,0.000498357,0.04079619,0.03532486,0.002458374,0.1376373,0.4048805],"study_design_scores_gemma":[0.0002242408,0.0006456486,0.538377,0.0008723428,0.0007371978,0.001209771,0.0005133595,0.01434228,0.03702309,0.001414059,0.4043815,0.0002594349],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.09138579,0.001856091,0.008266757,0.00004429292,0.0000197531,0.0002279649,0.8859773,0.001434157,0.01078804],"genre_scores_gemma":[0.09617542,0.001752801,0.009730502,0.00005395304,0.00001144207,0.0002763891,0.8889011,0.0002000657,0.002898272],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03672657,"threshold_uncertainty_score":0.07302558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01470415332617049,"score_gpt":0.2672614270061479,"score_spread":0.2525572736799774,"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."}}