{"id":"W3147509360","doi":"10.5194/gmd-14-5355-2021","title":"Cloud Feedbacks from CanESM2 to CanESM5.0 and their influence on climate sensitivity","year":2021,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Climate variability and models","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia; Ministry of Health; Environment and Climate Change Canada; University of Waterloo","funders":"","keywords":"Cloud forcing; Cloud feedback; Climate sensitivity; Shortwave; Longwave; Cloud fraction; Environmental science; Climatology; Cloud albedo; Climate model; Atmospheric sciences; Albedo (alchemy); Coupled model intercomparison project; Forcing (mathematics); Cloud cover; Cloud height; Cloud computing; Radiative transfer; Climate change; Geology; Computer science; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009170055,0.0002711881,0.0002511513,0.00004766124,0.0005223644,0.0001465039,0.0001721396,0.00009463406,0.000357927],"category_scores_gemma":[0.00007898306,0.000243455,0.00004043335,0.0003250566,0.0001657991,0.0001581853,0.0008374326,0.000153452,0.0005416095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003187344,"about_ca_system_score_gemma":0.0001315581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001213992,"about_ca_topic_score_gemma":0.008634877,"domain_scores_codex":[0.9974076,0.0000974519,0.0003375728,0.001132507,0.0004162069,0.0006087223],"domain_scores_gemma":[0.9988571,0.0001093891,0.00006059517,0.0005887513,0.00003962215,0.0003445188],"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":[0.0001633998,0.0006578417,0.02956365,0.00006574754,0.00004717137,0.0001349878,0.02839941,0.6949158,0.2140613,0.000642046,0.004006999,0.0273416],"study_design_scores_gemma":[0.001260705,0.000081078,0.2561271,0.0002969025,0.00004217337,0.00006968976,0.001208525,0.5316581,0.1363937,0.003890712,0.06652456,0.002446671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913503,0.00001010472,0.005692623,0.000579402,0.0004275754,0.0002524201,0.0002554067,0.00006137227,0.001370774],"genre_scores_gemma":[0.9896952,0.00001584255,0.007455932,0.001555306,0.00001726808,0.00003558908,0.00008314784,0.00001685806,0.001124868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2265635,"threshold_uncertainty_score":0.9927807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01469525195598422,"score_gpt":0.2107152097415772,"score_spread":0.1960199577855929,"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."}}