{"id":"W2032359234","doi":"10.3166/jesa.39.553-569","title":"Atmospheric pollution forecasting. Applications of horizontal and vertical vector fields","year":2005,"lang":"fr","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Horizontal and vertical; Environmental science; Atmospheric pollution; Meteorology; Pollution; Geology; Geography; Geodesy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0006730427,0.0005607014,0.0003760846,0.001005732,0.000230902,0.0009989357,0.0003204498,0.0006862904,0.007651194],"category_scores_gemma":[0.002215767,0.0003632455,0.0003946787,0.002192106,0.0002693355,0.001156389,0.0004598141,0.0004472952,0.001692645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002991873,"about_ca_system_score_gemma":0.0003318087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01341606,"about_ca_topic_score_gemma":0.006929293,"domain_scores_codex":[0.9998091,0.00005663906,0.00001379238,0.00003081615,0.00007461092,0.00001503834],"domain_scores_gemma":[0.9995109,0.0002498166,0.00004001226,0.00004396515,0.0001346372,0.0000206462],"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":[0.0001144245,0.00005757652,0.004888554,0.000200612,0.00005517355,0.00005627517,0.0000373543,0.1236465,0.003120685,0.01389309,0.01618502,0.8377448],"study_design_scores_gemma":[0.0000358531,0.00006121883,0.008725913,0.00009205235,0.00005217362,0.00009618324,0.00008642094,0.907515,0.002909889,0.03835377,0.04203606,0.00003541226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04398588,0.02207712,0.867253,0.003207909,0.002225986,0.0001516551,0.003484421,0.00545274,0.05216127],"genre_scores_gemma":[0.6609094,0.02552474,0.2692144,0.0004548319,0.001552767,0.000143503,0.003094351,0.0005300291,0.03857592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01341606,"threshold_uncertainty_score":0.02667594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308046124874677,"score_gpt":0.2533478682236583,"score_spread":0.2302674069749115,"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."}}