{"id":"W4205835295","doi":"10.5194/acp-22-951-2022","title":"Data assimilation of CrIS NH <sub>3</sub> satellite observations for improving spatiotemporal NH <sub>3</sub> distributions in LOTOS-EUROS","year":2022,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Rijksinstituut voor Volksgezondheid en Milieu; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Environmental science; Data assimilation; Ammonia; Atmospheric sciences; Meteorology; Chemistry; Biochemistry; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002850026,0.0002368396,0.0002994717,5.467182e-7,0.0004452995,0.00005292848,0.0003433759,0.00008208519,0.0001333698],"category_scores_gemma":[0.00006039948,0.0002598123,0.00007981902,0.0005762454,0.0001108479,0.0004553603,0.0001070329,0.0002582815,0.000003074602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002629217,"about_ca_system_score_gemma":0.0001541412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004250336,"about_ca_topic_score_gemma":0.0001760001,"domain_scores_codex":[0.9983109,0.00005201082,0.0004744589,0.000519298,0.0002781565,0.0003652318],"domain_scores_gemma":[0.9988093,0.0002127074,0.0002977663,0.0005060488,0.0000677739,0.0001063559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001516595,0.0002664366,0.2612457,0.0004899754,0.00006331482,0.000007973573,0.0003620163,0.01625308,0.1792373,0.00006625044,0.0006018686,0.5412545],"study_design_scores_gemma":[0.001234866,0.0001905378,0.2885575,0.00004265034,0.000166856,0.00001291678,0.0007591575,0.5645927,0.1371371,0.002120486,0.004409271,0.0007760114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881688,0.0003796229,0.007589983,0.0001189678,0.000103889,0.0003306154,0.002986492,0.00004343649,0.0002781689],"genre_scores_gemma":[0.9873626,0.0002410758,0.004179844,0.00007625092,0.000147692,0.00002563542,0.007909952,0.00001401021,0.00004289484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5483395,"threshold_uncertainty_score":0.9999854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02806018020685228,"score_gpt":0.2273087024719218,"score_spread":0.1992485222650696,"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."}}