{"id":"W4319083595","doi":"10.5194/acp-23-1893-2023","title":"Chemical and dynamical identification of emission outflows during the <i>HALO</i> campaign EMeRGe in Europe and Asia","year":2023,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Context (archaeology); Megacity; Pollution; Environmental science; Air pollution; Population; Outflow; Geography; Environmental protection; Atmospheric sciences; Meteorology; Chemistry; Economy; Ecology; Geology","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":[0.0002172159,0.0002870152,0.0002467245,0.0004832363,0.0003130653,0.0005516951,0.0001939348,0.0002846379,0.0007149769],"category_scores_gemma":[0.0001835811,0.0001183996,0.0003124099,0.0004736987,0.0001589572,0.0003011436,0.0005777213,0.0002676797,0.0002132799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002834285,"about_ca_system_score_gemma":0.0001697505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01503373,"about_ca_topic_score_gemma":0.02009316,"domain_scores_codex":[0.9999158,0.000008578802,0.000003799342,0.0000287741,0.00001582108,0.00002709927],"domain_scores_gemma":[0.999885,0.00001446793,0.00002754783,0.000008898372,0.00003762018,0.00002645727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006179437,0.0001542107,0.9381653,0.000112852,0.0001933302,0.0004884679,0.0007175328,0.003940338,0.04018119,0.0003773263,0.002212258,0.01283925],"study_design_scores_gemma":[0.000009348177,0.00004504262,0.9922007,0.0000109514,0.00002367744,0.00003928709,0.0002849288,0.003465786,0.002574503,0.00004019081,0.001296807,0.000008859839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962462,0.00005931844,0.0004360492,0.0000257917,0.000007632995,0.00001044594,0.001780692,0.00002737094,0.001406619],"genre_scores_gemma":[0.9944963,0.0000736513,0.0006406077,0.00003699527,0.00001075747,0.00001932193,0.004147578,0.00002728995,0.0005474955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01503373,"threshold_uncertainty_score":0.02989244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00543024516239676,"score_gpt":0.1959312187324495,"score_spread":0.1905009735700527,"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."}}