{"id":"W4416827581","doi":"10.1029/2024ms004645","title":"The Climatic Impacts of a Satellite‐Based Parameterization of the Wegener‐Bergeron‐Findeisen Process for Large‐Scale Models","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cloud computing; Cloud fraction; Cloud cover; Cloud top; Ice cloud; Satellite; Liquid water content; Scaling; Cloud height","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001687104,0.0008197637,0.0004235727,0.0002193249,0.0003805954,0.0007586541,0.0009389083,0.0006915395,0.0006434341],"category_scores_gemma":[0.004130144,0.0003644172,0.0007460002,0.0004013747,0.0004927567,0.001012635,0.000615203,0.001096868,0.000122842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009156199,"about_ca_system_score_gemma":0.0006995682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02430041,"about_ca_topic_score_gemma":0.01308218,"domain_scores_codex":[0.9995835,0.0002028492,0.00002884978,0.00007562886,0.00007223759,0.00003695994],"domain_scores_gemma":[0.9978055,0.001302485,0.0001924171,0.0003483217,0.0002573083,0.00009395584],"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":[0.0001905153,0.0001106879,0.01510867,0.00002709513,0.000091024,0.00002969241,0.00001789056,0.9735863,0.005347454,0.0007393346,0.0003354902,0.004415819],"study_design_scores_gemma":[0.00004891612,0.00004942207,0.004785026,0.000006438495,0.00002236708,0.000005746606,0.000009582761,0.991727,0.002726919,0.0002581079,0.0003435761,0.00001688321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9605808,0.0002955559,0.03403955,0.0003958507,0.0001061673,0.0000734999,0.0007390014,0.001053075,0.002716505],"genre_scores_gemma":[0.9916751,0.00005255482,0.007523594,0.00004015129,0.00001511814,0.00003371203,0.0003903697,0.0001202793,0.0001490195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02430041,"threshold_uncertainty_score":0.04831791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01337308156163268,"score_gpt":0.2805747887029294,"score_spread":0.2672017071412967,"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."}}