{"id":"W6966317216","doi":"10.3886/e164641","title":"Data and Code for: Global Life Insurers during a Low Interest Rate Environment","year":2022,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Booth University College","funders":"","keywords":"Interest rate; Life insurance; Debt; Fragility; Stock (firearms); Interest rate risk; Financial crisis; European union","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","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.002626624,0.001122875,0.001119237,0.0002922942,0.0005853667,0.000705352,0.01197943,0.0003938022,0.00418413],"category_scores_gemma":[0.001934782,0.00127333,0.00009022098,0.0003717278,0.0005026586,0.001826397,0.03985317,0.001110528,0.0007232257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008539285,"about_ca_system_score_gemma":0.0002902893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003377168,"about_ca_topic_score_gemma":0.001931472,"domain_scores_codex":[0.9926426,0.0002977828,0.001065015,0.003917484,0.0009031713,0.001173886],"domain_scores_gemma":[0.9834276,0.0002683974,0.001058094,0.01457057,0.00002608369,0.0006492231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004867258,0.0002528249,0.0002064247,0.0007310117,0.0005531708,0.0001688883,0.00001810388,0.0000163407,0.0002006437,0.00001217217,0.9972218,0.0001319135],"study_design_scores_gemma":[0.002293218,0.0001040602,0.0006363392,0.0002150909,0.0007346523,0.0001116809,0.0001275484,0.0003537896,0.0000132106,0.00002641466,0.9941495,0.001234469],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008176731,0.001498981,0.00002124298,0.0001759181,0.0006932288,0.00145902,0.9877934,0.0001759635,0.000005454659],"genre_scores_gemma":[0.000487459,0.002158556,0.0003267515,0.0004475148,0.0004001605,0.0001853696,0.9957056,0.0002511773,0.00003742831],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02787375,"threshold_uncertainty_score":0.9989716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1007693642459523,"score_gpt":0.3175230584669221,"score_spread":0.2167536942209697,"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."}}