{"id":"W4243158513","doi":"10.1002/9781119971528.ch9","title":"Select Mortality","year":2010,"lang":"en","type":"other","venue":"","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Annuity; Computer science; Life annuity; Economics; Pension; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001071843,0.0006247536,0.0004498224,0.002480892,0.000515112,0.001964159,0.0008663739,0.0005255968,0.4780635],"category_scores_gemma":[0.005008083,0.0002892064,0.0005907349,0.002781122,0.0001385624,0.001209663,0.001083021,0.001112453,0.3137226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007752409,"about_ca_system_score_gemma":0.001048844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004405525,"about_ca_topic_score_gemma":0.006274547,"domain_scores_codex":[0.9992079,0.00009901543,0.00004424934,0.00009681439,0.0004847696,0.00006724454],"domain_scores_gemma":[0.9984267,0.0004170685,0.0001102023,0.0002107361,0.0006427042,0.0001926016],"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":[0.00003452475,0.00001616671,0.0003605133,0.00005297858,0.000002245644,0.000007401913,0.00001391548,0.0001522682,0.00005614394,0.003390233,0.9509292,0.04498431],"study_design_scores_gemma":[0.00002608124,0.00001585399,0.003399975,0.00008929575,0.000003602544,0.00002291999,0.00002821833,0.0003702913,0.0002435795,0.003277047,0.9925117,0.00001143775],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001651067,0.0005915626,0.004728736,0.00192248,0.001032706,0.0002071607,0.2620406,0.005057575,0.7227681],"genre_scores_gemma":[0.01093925,0.001367882,0.006124679,0.001251796,0.0009884777,0.0004211793,0.3321596,0.003081148,0.6436661],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4780635,"threshold_uncertainty_score":0.7444791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02047061864393841,"score_gpt":0.335502567643795,"score_spread":0.3150319489998566,"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."}}