{"id":"W2618647913","doi":"10.1007/s00382-017-3736-4","title":"Evaluation of CORDEX-Arctic daily precipitation and temperature-based climate indices over Canadian Arctic land areas","year":2017,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ouranos; Environment and Climate Change Canada; Institut National de la Recherche Scientifique","funders":"National Oceanic and Atmospheric Administration; Rural Development Administration; ArcticNet; Natural Resources Canada; Canon Foundation for Scientific Research","keywords":"Climatology; Environmental science; Precipitation; Anomaly (physics); Arctic; Climate model; Climate extremes; Climate change; The arctic; Meteorology; Geography; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002128245,0.00117001,0.0005080199,0.0006324436,0.0007477511,0.001068169,0.0007813423,0.0003383779,0.0006630556],"category_scores_gemma":[0.002256255,0.0002471893,0.0004874265,0.0009891471,0.0002474774,0.0006100924,0.0004946367,0.0003266911,0.000107107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006068571,"about_ca_system_score_gemma":0.004870266,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8252191,"about_ca_topic_score_gemma":0.8172531,"domain_scores_codex":[0.9994494,0.000137039,0.00003414148,0.0001367219,0.0001586446,0.00008393786],"domain_scores_gemma":[0.9989741,0.0001415881,0.00008249386,0.00008476483,0.0006192424,0.00009774589],"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":[0.0009321227,0.0002555126,0.2000378,0.0001180309,0.0004225626,0.0001559396,0.0001770363,0.7528647,0.004808773,0.0007756975,0.002986284,0.03646554],"study_design_scores_gemma":[0.0001361324,0.0002128009,0.1546466,0.00002506044,0.0001476918,0.0000515568,0.0002180644,0.8333279,0.006965122,0.0001709108,0.00402926,0.0000689509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908547,0.0002412609,0.001807422,0.00008343744,0.00002779439,0.0000452901,0.003240784,0.000411261,0.003288136],"genre_scores_gemma":[0.9887801,0.0001384028,0.004579032,0.00003162664,0.000008849139,0.00003049605,0.005480627,0.00004560321,0.0009052021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1747809,"threshold_uncertainty_score":0.3516204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893626535369315,"score_gpt":0.2723226516328959,"score_spread":0.2533863862792027,"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."}}