{"id":"W3007492891","doi":"","title":"Potential causes of 15th century Arctic warming using coupled model simulations with data assimilation","year":2009,"lang":"en","type":"article","venue":"EGUGA","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climatology; Arctic; Proxy (statistics); Climate model; Data assimilation; Environmental science; Climate system; Climate change; The arctic; Forcing (mathematics); Global warming; General Circulation Model; Geography; Geology; Meteorology; Oceanography","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":[0.0001181194,0.00009744264,0.0001274606,0.00009097828,0.0001323033,0.00003744697,0.0001835595,0.00003735397,0.0001632312],"category_scores_gemma":[0.00006336738,0.0000794247,0.00001785194,0.000172781,0.00004187743,0.0004256137,0.00001335724,0.00006901969,0.000006098353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006535495,"about_ca_system_score_gemma":0.0000905684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005216814,"about_ca_topic_score_gemma":0.0009073078,"domain_scores_codex":[0.9991317,0.00003598563,0.0001776225,0.0002098398,0.0002562967,0.0001886015],"domain_scores_gemma":[0.9993501,0.0001060144,0.0001070377,0.0003325121,0.00004716586,0.00005720814],"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":[0.00008222333,0.00001656698,0.1510739,0.00001182339,0.00001003297,0.00000579065,0.00007769586,0.8464871,0.001162925,0.000007664689,0.000004348992,0.001059983],"study_design_scores_gemma":[0.0001668919,0.0000378504,0.3101575,0.00003092536,0.00004422572,0.000007962505,0.00002847883,0.6892926,0.00006113631,0.00008652762,0.00001134839,0.00007460322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946012,0.0001323492,0.004617694,0.00008146398,0.00006535975,0.0001055033,0.000250004,0.0000389191,0.0001075276],"genre_scores_gemma":[0.9910749,0.00002037921,0.008457366,0.00003673408,0.00004645313,5.056784e-8,0.000344762,0.000003666787,0.00001574168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1590837,"threshold_uncertainty_score":0.3238845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05329898208148268,"score_gpt":0.2820399113363171,"score_spread":0.2287409292548344,"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."}}