{"id":"W2084113589","doi":"10.1029/2007jd008658","title":"Evaluation of regional cloud climate simulations over Scandinavia using a 10‐year NOAA Advanced Very High Resolution Radiometer cloud climatology","year":2008,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Cloud cover; Environmental science; Climatology; Satellite; Cloud fraction; Cloud computing; Downwelling; Radiometer; Advanced very-high-resolution radiometer; Cloud top; Meteorology; Climate model; International Satellite Cloud Climatology Project; Atmospheric sciences; Longwave; Cloud albedo; Climate change; Remote sensing; Geography; Radiation; Geology; Computer science","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":[0.0008494306,0.00111461,0.0006155643,0.0003927879,0.000704371,0.0008269685,0.0007697854,0.001004935,0.0007924964],"category_scores_gemma":[0.001376801,0.0004857592,0.0008651315,0.0005846658,0.0004819225,0.0004481336,0.0003939098,0.0004037043,0.0001143586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001225984,"about_ca_system_score_gemma":0.000970392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1065676,"about_ca_topic_score_gemma":0.06285357,"domain_scores_codex":[0.9996979,0.0001106815,0.00002847044,0.00005626829,0.00003531643,0.00007143495],"domain_scores_gemma":[0.9990741,0.0004828242,0.00009951067,0.00006355735,0.0001808427,0.00009918532],"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":[0.0004984252,0.0002030931,0.02424191,0.00007012729,0.0001623803,0.0002686196,0.00009454007,0.9680402,0.001958557,0.0002462071,0.0002950572,0.003920992],"study_design_scores_gemma":[0.0003320143,0.000500566,0.02470481,0.00002671999,0.0001118948,0.00005208774,0.0001399485,0.9712351,0.002275743,0.0001079988,0.0004802843,0.00003294925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981673,0.0000869572,0.0004294837,0.00003627011,0.00001465695,0.00001429069,0.0003979921,0.00007542267,0.0007776284],"genre_scores_gemma":[0.9976721,0.000075986,0.001113447,0.00001850525,0.000005266642,0.00002001778,0.0008753396,0.00001945474,0.0001999055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1065676,"threshold_uncertainty_score":0.2118946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06971986563071153,"score_gpt":0.3552724772221583,"score_spread":0.2855526115914467,"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."}}