{"id":"W2048054824","doi":"10.1175/waf1011.1","title":"A Satellite-Based Fog Detection Scheme Using Screen Air Temperature","year":2007,"lang":"en","type":"article","venue":"Weather and Forecasting","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Geostationary orbit; Environmental science; Meteorology; Satellite; Depth sounding; Lapse rate; Remote sensing; Numerical weather prediction; Daytime; Geostationary Operational Environmental Satellite; Atmospheric sciences; Geology; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003082919,0.0004149948,0.0004407281,0.0009706833,0.0003351015,0.0004833678,0.0005312587,0.0002315374,0.0006050766],"category_scores_gemma":[0.0005552817,0.0002218456,0.0003277143,0.0004256224,0.0001783311,0.0003465424,0.00041676,0.0002493488,0.0001955591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006840348,"about_ca_system_score_gemma":0.0007205931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02703575,"about_ca_topic_score_gemma":0.03062127,"domain_scores_codex":[0.9998264,0.00001649424,0.00001101582,0.00004532266,0.00007437791,0.00002651447],"domain_scores_gemma":[0.9997296,0.00003136553,0.00003740843,0.00002666205,0.0001358162,0.00003913615],"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":[0.001556148,0.0003833243,0.1052283,0.0001795466,0.0003854343,0.0003117587,0.0002657768,0.2090631,0.2384115,0.001260687,0.005243663,0.4377107],"study_design_scores_gemma":[0.00006327156,0.0001345141,0.03242384,0.000009644325,0.00006801292,0.00009229041,0.00003365282,0.9396112,0.0261296,0.0002260541,0.001173891,0.00003402124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7054029,0.000194034,0.2864522,0.00009475491,0.0001122478,0.0002082117,0.0005120428,0.003972573,0.00305086],"genre_scores_gemma":[0.9239031,0.00002702851,0.07496957,0.00001888392,0.00001677822,0.0000303277,0.0003573206,0.00002110051,0.0006558996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02703575,"threshold_uncertainty_score":0.05375677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04558185910039515,"score_gpt":0.2370316896564841,"score_spread":0.191449830556089,"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."}}