{"id":"W2596417680","doi":"","title":"Considerations on domain location according to the jump of resolution between the driving data and the nested regional climate model within the Big-Brother experiment.","year":2015,"lang":"en","type":"article","venue":"2015 AGU Fall Meeting","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Jump; Nested set model; Domain (mathematical analysis); Brother; Mathematics; Computer science; Statistics; Geography; Environmental science; Econometrics; Data mining; Mathematical analysis; Physics; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01966133,0.0004441665,0.0004569952,0.0003991062,0.001214996,0.001832514,0.001923982,0.001626163,0.003695817],"category_scores_gemma":[0.06948645,0.0004335255,0.0005151549,0.0005333804,0.0008493472,0.002865294,0.00162399,0.002603819,0.0008220448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006482187,"about_ca_system_score_gemma":0.001142612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009363477,"about_ca_topic_score_gemma":0.01303029,"domain_scores_codex":[0.9941353,0.004105217,0.0003124355,0.0005556011,0.0006024909,0.0002889779],"domain_scores_gemma":[0.9729252,0.01715786,0.0009703847,0.005069878,0.003167473,0.0007091677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01194169,0.001338851,0.1491434,0.001101069,0.0009659004,0.001456445,0.002245832,0.2057676,0.09990335,0.2272397,0.08374471,0.2151514],"study_design_scores_gemma":[0.002067483,0.00169655,0.1127447,0.00111292,0.0006608529,0.001454607,0.004382472,0.5031872,0.1328226,0.1357509,0.1036124,0.0005073632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3685493,0.001945379,0.5359768,0.0323022,0.003741819,0.000741557,0.005670031,0.002165205,0.04890769],"genre_scores_gemma":[0.7853808,0.0003578942,0.2039242,0.003937447,0.0002814509,0.0004816669,0.001650218,0.0007426675,0.003243658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01966133,"threshold_uncertainty_score":0.1039803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1334100761764816,"score_gpt":0.3235265287372703,"score_spread":0.1901164525607888,"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."}}