{"id":"W4285591523","doi":"10.1029/2021ms002893","title":"Constraining Clouds and Convective Parameterizations in a Climate Model Using Paleoclimate Data","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"National Science Foundation","keywords":"Climate sensitivity; Paleoclimatology; Climatology; Climate model; Last Glacial Maximum; Forcing (mathematics); Environmental science; Precipitation; Atmospheric sciences; Meteorology; Holocene; Geology; Climate change; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00120712,0.0006737011,0.0004082313,0.0003061027,0.0005366719,0.0009790629,0.0007993403,0.0008454867,0.0005611711],"category_scores_gemma":[0.003253813,0.0005309514,0.0006074967,0.0004167306,0.000458879,0.001172675,0.0005861388,0.0009074637,0.00008449832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008222701,"about_ca_system_score_gemma":0.001076175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03869198,"about_ca_topic_score_gemma":0.02144678,"domain_scores_codex":[0.999725,0.0001117469,0.00001873014,0.00008174439,0.00002990629,0.00003284955],"domain_scores_gemma":[0.999089,0.0004540548,0.0001001379,0.0001762003,0.0001155982,0.0000648929],"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":[0.000121264,0.0001040146,0.01848079,0.00001268754,0.00008814611,0.00002430571,0.00002527361,0.9760302,0.001902031,0.0003546751,0.0001229871,0.002733599],"study_design_scores_gemma":[0.00005637313,0.00003045834,0.003026708,0.000002813897,0.00001881809,0.000004214426,0.00001233805,0.9951766,0.001233516,0.0002586347,0.000168912,0.00001066284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910384,0.0000687403,0.007243441,0.000155193,0.00002289512,0.00002377303,0.0004004107,0.0001475831,0.000899508],"genre_scores_gemma":[0.9954607,0.0000250053,0.004101643,0.00003311697,0.000005963667,0.00001893904,0.0002516243,0.00001774917,0.00008537367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03869198,"threshold_uncertainty_score":0.07693356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0840648819260655,"score_gpt":0.3233345291983867,"score_spread":0.2392696472723212,"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."}}