{"id":"W2086713197","doi":"10.3390/risks2040411","title":"Measuring Risk When Expected Losses Are Unbounded","year":2014,"lang":"en","type":"article","venue":"Risks","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Expected value; Expected shortfall; Coherent risk measure; Conditional probability; Value (mathematics); Value at risk; Pareto principle; Conditional expectation; Actuarial science; Mathematics; Econometrics; Mathematical economics; Computer science; Risk management; Statistics; Economics; Finance","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00190018,0.0001493063,0.0002735239,0.0002402192,0.0003230424,0.0003950624,0.0005354651,0.0001050037,0.0004831796],"category_scores_gemma":[0.004887575,0.0001111363,0.0001075265,0.000517243,0.00006931139,0.0003288432,0.00007944752,0.0001628722,0.00100614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002808919,"about_ca_system_score_gemma":0.00003536947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004483306,"about_ca_topic_score_gemma":0.0002699847,"domain_scores_codex":[0.9973332,0.0004034552,0.0004945652,0.0004468742,0.00105965,0.000262291],"domain_scores_gemma":[0.9976091,0.0006530494,0.0004873392,0.0007406915,0.0003719688,0.0001378093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004566103,0.00006445456,0.8176877,0.000002035749,0.00002644702,0.000005738316,0.001403561,0.01085695,0.00006194736,0.0009797221,0.02635038,0.1425153],"study_design_scores_gemma":[0.0008629878,0.0000754079,0.6685822,0.00002941051,0.00004671211,0.000009265872,0.0008887055,0.02901773,0.001821859,0.112048,0.1861504,0.0004672435],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8378683,0.000359745,0.1339118,0.0002882422,0.0007010284,0.0001731204,0.00001554612,0.0001889353,0.02649323],"genre_scores_gemma":[0.9935503,0.0002650486,0.003939196,0.00009155859,0.0002542699,0.000008616544,0.000004773302,0.00001684802,0.001869407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1598,"threshold_uncertainty_score":0.9997717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2410636190463804,"score_gpt":0.3731557394998607,"score_spread":0.1320921204534803,"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."}}