{"id":"W2913933910","doi":"10.1111/jori.12276","title":"Correlated Trading by Life Insurers and Its Impact on Bond Prices","year":2019,"lang":"en","type":"article","venue":"Journal of Risk & Insurance","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bond; Quarter (Canadian coin); Business; Monetary economics; Life insurance; Value (mathematics); Financial economics; Economics; Finance; Actuarial science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008816127,0.0002242423,0.0006593221,0.0003052482,0.0001071341,0.00008624089,0.0002581383,0.0001233098,0.00008825919],"category_scores_gemma":[0.0002385444,0.000200653,0.0002115027,0.0003422642,0.0000290968,0.0005804523,0.00002412766,0.0005133994,0.0002319556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001393314,"about_ca_system_score_gemma":0.00002924153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008203238,"about_ca_topic_score_gemma":0.000002310993,"domain_scores_codex":[0.9984005,0.0000167065,0.0008861793,0.0002676774,0.0001133762,0.0003155385],"domain_scores_gemma":[0.9979091,0.0001198515,0.001560612,0.0001854212,0.00007399321,0.0001510513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004973997,0.0001961477,0.9702208,0.00005276185,0.0002279411,0.00001775779,0.0009334969,0.0009543113,0.0001171452,0.01542486,0.006664375,0.004692999],"study_design_scores_gemma":[0.001953494,0.0006377244,0.9696772,0.0001147757,0.0000149175,0.00001409521,0.00008253106,0.001299102,0.0001075091,0.002483051,0.02328634,0.0003293363],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765962,0.0174311,0.0001690926,0.0001447958,0.0009571309,0.0001872956,0.0002288673,0.00001238575,0.004273117],"genre_scores_gemma":[0.9905067,0.008902795,0.00009749258,0.0002274534,0.0001218304,0.000002074527,0.000002215937,0.00002717227,0.0001122797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01662197,"threshold_uncertainty_score":0.8182392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01017277467346075,"score_gpt":0.2179390381219581,"score_spread":0.2077662634484973,"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."}}