{"id":"W4389832722","doi":"10.1002/9781119700357.ch6","title":"Extratropical Cloud Feedbacks","year":2023,"lang":"en","type":"other","venue":"Geophysical monograph","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Pacific Northwest National Laboratory; Lawrence Livermore National Laboratory; Nuclear Safety and Security Commission; Battelle; University of Wyoming; National Aeronautics and Space Administration; U.S. Department of Energy; National Science Foundation","keywords":"Extratropical cyclone; Cloud feedback; Environmental science; Context (archaeology); Shortwave; Climatology; Longwave; Climate model; Positive feedback; Global warming; Cloud computing; Climate change; Cloud cover; Cloud forcing; Cloud height; Atmospheric sciences; Climate sensitivity; Geography; Computer science; Geology; Radiative transfer; Physics; Ecology; Biology","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":[0.0001488829,0.0002977872,0.0002033901,0.0005606717,0.0003882163,0.001091454,0.0003731019,0.000186356,0.01654959],"category_scores_gemma":[0.0002849583,0.0000810932,0.0002367628,0.001244965,0.0002667013,0.0008565318,0.0008921003,0.0004530047,0.001710849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008372946,"about_ca_system_score_gemma":0.0009173848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01543795,"about_ca_topic_score_gemma":0.02950744,"domain_scores_codex":[0.9999008,0.000007039377,0.000004187416,0.00002133139,0.00004810807,0.0000184626],"domain_scores_gemma":[0.999885,0.0000226202,0.00002145114,0.00001448662,0.00003404877,0.00002241249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001669795,0.0001080854,0.03920997,0.003491511,0.0001134792,0.001204296,0.001019774,0.008548738,0.02679827,0.08138498,0.07821409,0.7597398],"study_design_scores_gemma":[0.0000202103,0.00002777192,0.09592479,0.0003716653,0.00004768617,0.0005237194,0.0004255823,0.002172385,0.00308071,0.02358165,0.8737978,0.00002593906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1546803,0.1701488,0.007574966,0.004863327,0.001585741,0.0001759927,0.009269169,0.001148,0.6505537],"genre_scores_gemma":[0.6882709,0.1655558,0.004616577,0.001797796,0.00143248,0.00007385666,0.005142311,0.0002741911,0.1328361],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01654959,"threshold_uncertainty_score":0.05536389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005771560258282253,"score_gpt":0.2076957105349802,"score_spread":0.201924150276698,"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."}}