{"id":"W2035142461","doi":"10.1029/2002jd002285","title":"Variability of the Arctic atmospheric moisture budget from TOVS satellite data","year":2002,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Climate variability and models","field":"Environmental Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Precipitation; Climatology; Arctic; Precipitable water; Arctic oscillation; Atmospheric sciences; North Atlantic oscillation; Moisture; Storm track; Storm; Oceanography; Geology; Geography; Meteorology; Northern Hemisphere","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002407799,0.0001803143,0.0004188774,0.000002682285,0.0002049226,0.00006751953,0.002356279,0.0001240679,0.006112745],"category_scores_gemma":[0.002811603,0.0001113436,0.0002218897,0.0007455236,0.001028258,0.0005297487,0.001727249,0.001081216,0.0001842648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002651888,"about_ca_system_score_gemma":0.00005648075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00572999,"about_ca_topic_score_gemma":0.0003801435,"domain_scores_codex":[0.9955164,0.0009801005,0.0006793035,0.0004421367,0.00186533,0.0005166824],"domain_scores_gemma":[0.9955357,0.00203988,0.0003172237,0.001674483,0.0001669984,0.0002657239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007523514,0.005873562,0.8288094,0.0002055659,0.0004001831,0.0000673728,0.002734284,0.005433144,0.03606649,0.001336567,0.0305507,0.08777038],"study_design_scores_gemma":[0.0008661968,0.0005126527,0.8625461,0.0001585277,0.00008781056,0.00001355065,0.0002924095,0.03381962,0.000664155,0.07070266,0.03005874,0.0002775638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931613,0.0003344614,0.0002282278,0.001636186,0.0001756849,0.0002461811,0.00005192064,0.000007559132,0.004158502],"genre_scores_gemma":[0.994041,0.0003271163,0.004733768,0.00008858462,0.0002254739,0.000002929982,0.000003138243,0.00001731827,0.0005607223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08749282,"threshold_uncertainty_score":0.9947958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05806895998474022,"score_gpt":0.3070801342315561,"score_spread":0.2490111742468159,"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."}}