{"id":"W3033512961","doi":"10.1139/cjp-2020-0561","title":"Impact of global data assimilation system atmospheric models on astroparticle showers","year":2021,"lang":"en","type":"preprint","venue":"Canadian Journal of Physics","topic":"Astrophysics and Cosmic Phenomena","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vicerrectoría de Investigación y Extensión, Universidad Industrial de Santander; Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas; Universidad Industrial de Santander; CYTED Ciencia y Tecnología para el Desarrollo; Ministerio de Ciencia e Innovación","keywords":"Data assimilation; Environmental science; Flux (metallurgy); Meteorology; Atmospheric research; Observatory; Auger; Atmospheric sciences; Atmospheric models; Atmospheric model; Physics; Atmosphere (unit); Astrophysics; Materials science; Atomic physics","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":[0.001108048,0.0008349821,0.0006038864,0.0003216235,0.0005339556,0.0009354514,0.0008711519,0.0008381766,0.001161571],"category_scores_gemma":[0.002316834,0.0003421978,0.0009654472,0.0004645807,0.0003984342,0.000774538,0.0007063081,0.0008695356,0.0001221553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009378077,"about_ca_system_score_gemma":0.001211857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06532953,"about_ca_topic_score_gemma":0.03900309,"domain_scores_codex":[0.9996436,0.0001454615,0.00002025278,0.00008331759,0.00005862158,0.00004875535],"domain_scores_gemma":[0.9993103,0.0003074495,0.00007704078,0.0001207448,0.0001306305,0.00005376523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005045307,0.00004556095,0.01224834,0.00002099095,0.0001035083,0.00003567999,0.00003130561,0.9814091,0.00130582,0.001116233,0.0002644424,0.003368678],"study_design_scores_gemma":[0.00003403484,0.00003190117,0.003495286,0.000005599414,0.00002755374,0.000008851001,0.00001812903,0.9942215,0.001227047,0.0003899757,0.0005269774,0.00001308597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9092413,0.0003276805,0.07968338,0.0005681207,0.0001899092,0.00009315979,0.00244508,0.001461176,0.005990256],"genre_scores_gemma":[0.9832031,0.00007664936,0.0152669,0.00007306821,0.00002181735,0.00004502736,0.0006994972,0.0001944432,0.0004195317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06532953,"threshold_uncertainty_score":0.1298985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03208664486319406,"score_gpt":0.2612388285125773,"score_spread":0.2291521836493833,"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."}}