{"id":"W3031348766","doi":"10.1029/2020ea001149","title":"A Flow‐Dependent Targeted Observation Method for Ensemble Kalman Filter Assimilation Systems","year":2020,"lang":"en","type":"article","venue":"Earth and Space Science","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"National Natural Science Foundation of China","keywords":"Data assimilation; Spurious relationship; Kalman filter; Covariance; Ensemble Kalman filter; Computer science; Predictability; Algorithm; Environmental science; Statistics; Mathematics; Meteorology; Extended Kalman filter; Machine learning; Artificial intelligence","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":[0.0006758496,0.0005149679,0.0004232998,0.0003172707,0.0002861054,0.0003544213,0.0005386609,0.0004451915,0.0008302595],"category_scores_gemma":[0.001700277,0.0002710794,0.0005308829,0.0002893583,0.000290723,0.0006381634,0.0005870993,0.0006290265,0.0001743971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004207623,"about_ca_system_score_gemma":0.001212704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009456368,"about_ca_topic_score_gemma":0.00907646,"domain_scores_codex":[0.9996827,0.00009291541,0.000017202,0.00007421135,0.0001079237,0.00002506099],"domain_scores_gemma":[0.9995216,0.0001941772,0.00005878249,0.00003989723,0.0001690589,0.00001650753],"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":[0.00006244296,0.00004237074,0.001506413,0.00005627614,0.00008751535,0.00003715219,0.00007714405,0.8222116,0.01412844,0.01453091,0.0006306948,0.1466291],"study_design_scores_gemma":[0.000002521611,0.00001151287,0.0001349113,0.000001710963,0.000004309273,0.000004228395,0.00000173939,0.9982105,0.000640125,0.0006873933,0.000297868,0.00000311353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003434079,0.00002464468,0.996223,0.00001224411,0.000006648687,0.000006184446,0.000008616127,0.00006144596,0.0002231653],"genre_scores_gemma":[0.4184029,0.0001461226,0.5795871,0.00005256195,0.00005118492,0.0001482061,0.0001493442,0.00008834359,0.001374226],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009456368,"threshold_uncertainty_score":0.01880264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05784960316263048,"score_gpt":0.2626648038778731,"score_spread":0.2048152007152426,"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."}}