{"id":"W1990209519","doi":"10.1080/17442508.2010.523467","title":"Randomized stopping times and coherent multiperiod risk measures","year":2010,"lang":"en","type":"article","venue":"Stochastics","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Representation (politics); Randomized controlled trial; Stopping time; Feature (linguistics); Optimal stopping; Computer science; Mathematics; Statistics; Medicine; Philosophy; Linguistics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002945243,0.0001414674,0.0004037455,0.000161052,0.0002513076,0.0002559085,0.0002327646,0.0001004345,0.0001794223],"category_scores_gemma":[0.01019962,0.00009484464,0.00009324356,0.0002128927,0.000279898,0.0001334247,0.00007381044,0.0002569556,0.00008264941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005307093,"about_ca_system_score_gemma":0.0000500262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005671984,"about_ca_topic_score_gemma":0.00008779686,"domain_scores_codex":[0.9980987,0.0001923135,0.0004925006,0.0003099461,0.0007208479,0.0001856465],"domain_scores_gemma":[0.9972818,0.001609646,0.000295756,0.0003583252,0.0003188448,0.0001356151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0156001,0.0001758486,0.01630374,0.000005513295,0.0001879833,0.00001306032,0.008767339,0.03295054,0.002175703,0.03372902,0.008013053,0.8820781],"study_design_scores_gemma":[0.1136563,0.0001065999,0.004039753,0.00002239222,0.0002271233,0.00003551404,0.001026218,0.7446887,0.0004901757,0.0640351,0.07094382,0.0007282857],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2419407,0.0003663645,0.7521841,0.0002056847,0.001306044,0.0005498042,0.00002800617,0.00006613789,0.003353203],"genre_scores_gemma":[0.9814999,0.0003773866,0.01690055,0.000050245,0.0001689364,0.00002003672,0.000003778814,0.00001276147,0.0009663727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8813498,"threshold_uncertainty_score":0.9981379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04385878517443498,"score_gpt":0.3425239926315008,"score_spread":0.2986652074570658,"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."}}