{"id":"W2099875328","doi":"10.1175/jcli4008.1","title":"Estimation of the Impact of Sampling Errors in the VOS Observations on Air–Sea Fluxes. Part II: Impact on Trends and Interannual Variability","year":2007,"lang":"en","type":"article","venue":"Journal of Climate","topic":"Climate variability and models","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centers for Disease Control and Prevention; National Oceanic and Atmospheric Administration; Russian Foundation for Basic Research; Deutsche Forschungsgemeinschaft","keywords":"Climatology; Environmental science; Latitude; Data assimilation; Zonal and meridional; Atmosphere (unit); Flux (metallurgy); Forcing (mathematics); Thermohaline circulation; Ocean current; Geology; Oceanography; Geography; Meteorology","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":[],"consensus_categories":[],"category_scores_codex":[0.003948417,0.0001271792,0.0002539675,0.00008975718,0.0001087036,0.00001253886,0.0002476985,0.0000624601,0.0001653616],"category_scores_gemma":[0.0003844974,0.00006319468,0.0002276637,0.0003610509,0.0001617873,0.0002656836,0.00008289127,0.0002754408,9.840088e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002395889,"about_ca_system_score_gemma":0.00002425586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003017812,"about_ca_topic_score_gemma":0.00006632177,"domain_scores_codex":[0.9984051,0.0001772118,0.0007184113,0.0001195287,0.0003672537,0.0002124684],"domain_scores_gemma":[0.9984275,0.0006848313,0.0005338595,0.0002702092,0.00002607547,0.00005759012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0005192511,0.0007516114,0.3261752,0.00001921253,0.00002920612,0.000001221997,0.004510816,0.6587809,0.002439715,0.0002518484,0.0001296621,0.006391262],"study_design_scores_gemma":[0.0004049358,0.0006971394,0.9761729,0.000109083,0.00002686699,0.00001294743,0.0001454089,0.02035156,0.0003835117,0.001613909,0.00002058721,0.00006111258],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978688,0.000003604129,0.0002101042,0.0005935543,0.00007717683,0.000118021,0.00006861325,0.000002643485,0.001057447],"genre_scores_gemma":[0.9995538,0.00001862292,0.0003256259,0.00006471323,0.00002343052,0.000001073902,0.000003150613,0.000005696364,0.000003864221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6499977,"threshold_uncertainty_score":0.2577004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04670774705116535,"score_gpt":0.3421503105215729,"score_spread":0.2954425634704075,"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."}}