{"id":"W1578667964","doi":"10.1002/9780470012505.taa016","title":"Aggregate Loss Modeling","year":2004,"lang":"en","type":"other","venue":"Encyclopedia of Actuarial Science","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Aggregate (composite); Environmental science; Materials science; Nanotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004649897,0.0003752123,0.0007656569,0.001017719,0.0002282189,0.000209557,0.004193292,0.0003868573,0.00262724],"category_scores_gemma":[0.005445257,0.0002615644,0.0002466639,0.002143876,0.001972863,0.0005893452,0.0006573348,0.0003731526,0.000654382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001436135,"about_ca_system_score_gemma":0.002666442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00137706,"about_ca_topic_score_gemma":0.0003073906,"domain_scores_codex":[0.9927606,0.000104762,0.001023263,0.001388755,0.004046014,0.0006766137],"domain_scores_gemma":[0.9965193,0.0002927883,0.0008172411,0.001631972,0.0004040751,0.0003346043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004483113,0.001522149,0.001201147,0.0003199257,0.0001689547,0.0001786033,0.0129564,0.1122352,0.0008484633,0.2102602,0.3281639,0.3316967],"study_design_scores_gemma":[0.0008803768,0.0001494599,0.00005304867,0.0004754824,0.00004616119,0.00001306341,0.0001321826,0.01118593,0.000209634,0.4279438,0.5579669,0.0009439274],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002673553,0.0005352717,0.02733906,0.0003402514,0.003824588,0.0004982612,0.00006492364,0.0001347614,0.9645893],"genre_scores_gemma":[0.2655924,0.003842051,0.02603584,0.0001833035,0.003137527,0.00003526485,0.00001021816,0.0003979211,0.7007655],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3307528,"threshold_uncertainty_score":0.9999837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0525857967882727,"score_gpt":0.3487626085712427,"score_spread":0.29617681178297,"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."}}