{"id":"W3112906047","doi":"","title":"A fast, flexible, approximate technique for computing radiative transfer in inhomogeneous cloud fields","year":2003,"lang":"en","type":"article","venue":"EGS - AGU - EUG Joint Assembly","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Radiative transfer; Cloud computing; Benchmark (surveying); Statistical physics; Scale (ratio); Computer science; Radiative flux; Meteorology; Environmental science; Remote sensing; Applied mathematics; Physics; Mathematics; Geology; Optics","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":[0.0005094992,0.0006226968,0.0005773465,0.0004005906,0.0006427088,0.0006618249,0.001245914,0.0006692784,0.002635443],"category_scores_gemma":[0.002183802,0.0002994419,0.0004982285,0.0008738622,0.0004018589,0.0009540352,0.0008771552,0.001143877,0.0010282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004449899,"about_ca_system_score_gemma":0.0007277823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004442654,"about_ca_topic_score_gemma":0.006683585,"domain_scores_codex":[0.9997764,0.00003074754,0.000008097434,0.00002807906,0.000134707,0.00002194741],"domain_scores_gemma":[0.9996158,0.0001217539,0.00003406958,0.0001211736,0.0000828313,0.00002430424],"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":[0.0001794897,0.00008620464,0.001501579,0.0001783926,0.00008775687,0.0001607299,0.0001411285,0.5351365,0.03886789,0.05252123,0.009280303,0.3618588],"study_design_scores_gemma":[0.00001779212,0.00001625292,0.0002433384,0.000004420103,0.000007204862,0.00003345044,0.000005167772,0.9877401,0.003081764,0.005956692,0.002884908,0.00000886936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003401234,0.00007086164,0.9947056,0.00003610351,0.00003111379,0.00002341029,0.00007143819,0.0009862729,0.0006740461],"genre_scores_gemma":[0.1413099,0.0001751677,0.8558424,0.00006832511,0.00007262399,0.0001571009,0.0003144387,0.0003725227,0.001687576],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004442654,"threshold_uncertainty_score":0.008833587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0164619910937574,"score_gpt":0.2417214296686504,"score_spread":0.225259438574893,"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."}}