{"id":"W7140290529","doi":"10.22541/essoar.172656822.29991402/v1","title":"Assessing Cloud Fraction in the Canadian Regional Climate Model Over North America Using Satellite Data and a Satellite Simulator Package","year":2024,"lang":"","type":"article","venue":"","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; GDG Environnement; Université du Québec à Montréal","funders":"Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Satellite; Cloud computing; Climate model; Earth observation satellite; Cloud fraction; Fraction (chemistry); Cloud cover","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0008477641,0.0009678242,0.0005443977,0.0006726713,0.001154287,0.001170478,0.001910553,0.0006204288,0.001519484],"category_scores_gemma":[0.001625766,0.0004748276,0.0009329693,0.001409079,0.0003789255,0.0005748366,0.000459916,0.0006469862,0.0002398119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01097618,"about_ca_system_score_gemma":0.01130674,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9653881,"about_ca_topic_score_gemma":0.9454305,"domain_scores_codex":[0.9996846,0.00004884913,0.00001969536,0.00009249918,0.0000880109,0.00006631973],"domain_scores_gemma":[0.9991834,0.0001387872,0.00005951841,0.00005214564,0.0004900337,0.00007611882],"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":[0.0001585192,0.00008153617,0.04533806,0.0000890217,0.0001810633,0.00006750304,0.0000763586,0.940402,0.001374975,0.001121736,0.003742394,0.007366671],"study_design_scores_gemma":[0.00009449083,0.00002879187,0.03530269,0.00001931727,0.00006432999,0.00001966696,0.00008614777,0.9601457,0.0007636361,0.0002195181,0.00320223,0.00005358686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9629912,0.0005212229,0.005648174,0.0003966172,0.00007668355,0.0001290928,0.01917109,0.0009687744,0.01009711],"genre_scores_gemma":[0.9795939,0.000303787,0.008705433,0.00008831941,0.00001431255,0.00006097338,0.00971106,0.0001204592,0.001401789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03461188,"threshold_uncertainty_score":0.07963812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1008503114775157,"score_gpt":0.3327999479397837,"score_spread":0.231949636462268,"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."}}