{"id":"W4391463434","doi":"10.1016/j.jqsrt.2024.109123","title":"Monte Carlo simulation of atmospheric radiative forcings using a path-integral formulation approach for spectro-radiative sensitivities","year":2024,"lang":"en","type":"article","venue":"Journal of Quantitative Spectroscopy and Radiative Transfer","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Agence Nationale de la Recherche","keywords":"Radiative transfer; Monte Carlo method; Atmospheric sciences; Atmospheric radiative transfer codes; Environmental science; Computational physics; Statistical physics; Physics; Mathematics; Statistics; 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":[0.0009156059,0.0004863228,0.0008031306,0.0007073685,0.001018418,0.00117373,0.001427169,0.001926095,0.003119771],"category_scores_gemma":[0.003394703,0.0009020478,0.0007948777,0.0008998892,0.0008619587,0.001012209,0.0007473187,0.001265207,0.0002641887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001577489,"about_ca_system_score_gemma":0.001956963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04691508,"about_ca_topic_score_gemma":0.02908468,"domain_scores_codex":[0.9997126,0.0001165522,0.00001456932,0.0000411795,0.00006779512,0.00004726687],"domain_scores_gemma":[0.9978676,0.001544815,0.0001373569,0.00009561263,0.0002476767,0.000106959],"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":[0.00001251505,0.0000188098,0.0002667824,0.000005099474,0.000008621251,0.00001389015,0.000009414281,0.9964942,0.0001793814,0.002392092,0.00006767431,0.0005315093],"study_design_scores_gemma":[0.000003383497,0.000001518431,0.00003232711,6.944501e-7,0.000001170191,0.000001438166,0.000001574053,0.9995824,0.0000521145,0.0002865081,0.00003497014,0.000001921147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4105042,0.0004951163,0.5635621,0.001001801,0.0002222853,0.0001792339,0.0007092616,0.001216383,0.02210959],"genre_scores_gemma":[0.9404023,0.0001372103,0.05577459,0.0001385533,0.00004500191,0.000144318,0.0002825481,0.0001995915,0.002875816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04691508,"threshold_uncertainty_score":0.09328401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01800635037495763,"score_gpt":0.2794385129536848,"score_spread":0.2614321625787271,"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."}}