{"id":"W1990345816","doi":"10.1007/s003820050337","title":"A transient climate change simulation with greenhouse gas and aerosol forcing: experimental design and comparison with the instrumental record for the twentieth century","year":2000,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":200,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria; Environment and Climate Change Canada; Canadian Forest Service","funders":"","keywords":"Forcing (mathematics); Greenhouse gas; Climatology; Aerosol; Environmental science; Climate model; Climate change; Sulfate aerosol; Precipitation; Transient climate simulation; Atmospheric sciences; Cloud forcing; Radiative forcing; Global warming; Climate commitment; Meteorology; Effects of global warming; Geography; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003569536,0.000243267,0.0002045495,0.00001555832,0.0007003229,0.0001204095,0.000149587,0.00006532003,0.0001002598],"category_scores_gemma":[0.000002093073,0.0001365793,0.00003790727,0.0001085904,0.0004418828,0.0003266343,0.0000876578,0.0001271042,0.000004731339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001410004,"about_ca_system_score_gemma":0.000004414087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001408365,"about_ca_topic_score_gemma":0.0007493083,"domain_scores_codex":[0.9986259,0.00006968676,0.0002245714,0.0004092345,0.0002129256,0.0004576683],"domain_scores_gemma":[0.9993132,0.0002215875,0.0001012644,0.0002679296,0.000007740987,0.00008832425],"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":[0.01349431,0.001992801,0.1403805,0.0003981438,0.0002092719,0.00001284189,0.05094826,0.5507153,0.002132677,0.001268213,0.0001217214,0.238326],"study_design_scores_gemma":[0.001404296,0.0008700446,0.003358557,0.00003965252,0.00009275128,0.0000166902,0.002349278,0.9910653,0.00007989982,0.00002013419,0.0004687903,0.0002346538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884279,0.00009319123,0.008571994,0.0004993327,0.00005008149,0.002043422,0.00008551174,0.00005060098,0.0001779432],"genre_scores_gemma":[0.9962936,0.0008310989,0.002308038,0.0002136505,0.00001905303,0.0002499468,0.00003782423,0.0000362881,0.00001051582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.44035,"threshold_uncertainty_score":0.5569541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03218897810715259,"score_gpt":0.255925339848745,"score_spread":0.2237363617415924,"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."}}