{"id":"W1803078767","doi":"10.1007/s00382-002-0288-y","title":"Factors contributing to diurnal temperature range trends in twentieth and twenty-first century simulations of the CCCma coupled model","year":2003,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":159,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"National Research Council Canada","keywords":"Environmental science; Climatology; Atmospheric sciences; Cloud cover; Northern Hemisphere; Latitude; Diurnal temperature variation; Snow; Climate model; Climate change; Geology; Meteorology; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007548774,0.0003214709,0.0003031283,0.0004348394,0.0009235739,0.00121937,0.0004508794,0.00110499,0.001453949],"category_scores_gemma":[0.006549967,0.0005448904,0.0004441775,0.000731425,0.0005352708,0.0006816997,0.000552187,0.0009896627,0.000143748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293964,"about_ca_system_score_gemma":0.00117787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0893092,"about_ca_topic_score_gemma":0.1107317,"domain_scores_codex":[0.9998013,0.00005475303,0.00001850222,0.00004711138,0.00002163521,0.00005661005],"domain_scores_gemma":[0.9984075,0.0008374728,0.0001909391,0.0001006309,0.0002774436,0.0001860311],"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":[0.0004383751,0.000152968,0.2469312,0.00007788568,0.0001859523,0.0004265444,0.0003986385,0.7357177,0.006952019,0.002216708,0.002152296,0.004349744],"study_design_scores_gemma":[0.000123467,0.00007133479,0.1922673,0.00002326283,0.0001100774,0.00008912811,0.0004378456,0.8017788,0.00254375,0.0007796808,0.001702877,0.00007261955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979408,0.00008368186,0.000363354,0.0002935792,0.00002498316,0.000004442397,0.0002714195,0.00003045748,0.0009871231],"genre_scores_gemma":[0.9994211,0.00004246113,0.00009668537,0.00002062351,0.000005482287,0.000003762797,0.0002198599,0.00001670628,0.0001733091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0893092,"threshold_uncertainty_score":0.1775787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01532697157569214,"score_gpt":0.2452763784491615,"score_spread":0.2299494068734694,"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."}}