{"id":"W2272377578","doi":"10.1002/wilm.10509","title":"A Note on Jointly Backtesting Models for Multiple Assets and Horizons","year":2016,"lang":"en","type":"article","venue":"Wilmott","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; HEC Montréal","funders":"","keywords":"Econometrics; Economics; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0008370564,0.0001312269,0.000161246,0.00009437949,0.0005109856,0.00007873306,0.000183158,0.00007790792,0.0000144731],"category_scores_gemma":[0.0004818612,0.0001014688,0.00008685028,0.0001612472,0.0002141985,0.0002810214,0.00005111384,0.00006140811,0.00002862236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005862521,"about_ca_system_score_gemma":0.000042686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000630827,"about_ca_topic_score_gemma":0.001699936,"domain_scores_codex":[0.9986237,0.00009380106,0.0001879099,0.0003449942,0.0003194694,0.0004301688],"domain_scores_gemma":[0.9989675,0.0005079617,0.00009381145,0.0002247075,0.00008737135,0.0001186279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001659748,0.0003792437,0.1866282,0.0001248394,0.0001275547,0.00002219605,0.007717512,0.0001873439,0.001701064,0.3529634,0.01385523,0.4361275],"study_design_scores_gemma":[0.007884467,0.00108211,0.3699282,0.0009013446,0.0002174798,0.000003474986,0.002270449,0.01435973,0.000749351,0.2773111,0.3230948,0.00219755],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8986921,0.0001369448,0.03389396,0.00526931,0.0009725823,0.001760092,0.0001226805,0.0003520054,0.05880034],"genre_scores_gemma":[0.9942001,0.00009110341,0.004417258,0.0001963372,0.0002544674,0.00007223321,0.000001624154,0.00001934709,0.0007475987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4339299,"threshold_uncertainty_score":0.4137776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04234564887444071,"score_gpt":0.3137832470106088,"score_spread":0.2714375981361681,"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."}}