{"id":"W2110460416","doi":"10.1109/lcomm.2006.1613731","title":"Estimation of typical sum of lognormal random variables using log shifted gamma approximation","year":2006,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Log-normal distribution; Random variable; Statistics; Mathematics; Gamma distribution; Applied mathematics; Algorithm; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002277043,0.0001091278,0.0003225359,0.0002715064,0.0001876303,0.00004954012,0.001284356,0.00009625366,0.00002461673],"category_scores_gemma":[0.0006767357,0.00009115285,0.0001224221,0.0007031977,0.0005801637,0.0004616206,0.000154905,0.0001557553,0.000008884159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004678954,"about_ca_system_score_gemma":0.00006951466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003254524,"about_ca_topic_score_gemma":0.0000679932,"domain_scores_codex":[0.9973987,0.0006156207,0.001072546,0.0002060689,0.0005509306,0.0001560858],"domain_scores_gemma":[0.9955487,0.001780893,0.0005686565,0.00181443,0.0002556989,0.00003159802],"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":[0.0002880656,0.0006167789,0.007548001,0.00004456969,0.00003969072,4.47301e-7,0.0007226594,0.8701764,0.07122428,0.03754014,0.001366787,0.01043222],"study_design_scores_gemma":[0.0008153393,0.00001580747,0.007183882,0.00004025664,0.00003887772,0.000004156658,0.00005161508,0.9296724,0.00935859,0.05254668,0.0001524319,0.0001200209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.51683,0.00007470317,0.4810558,0.001505374,0.00006228881,0.0001835061,0.00001555971,0.00001728754,0.000255432],"genre_scores_gemma":[0.897406,0.000008961427,0.1024145,0.00009016196,0.00001852233,0.00001197335,0.00003190014,0.00000649094,0.00001154317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.380576,"threshold_uncertainty_score":0.3717105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1159723864968925,"score_gpt":0.3563638372105259,"score_spread":0.2403914507136335,"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."}}