{"id":"W4229739175","doi":"10.1002/9781119971528.ch3","title":"The Life Table","year":2010,"lang":"es","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":"Table (database); Notation; Terminology; Life expectancy; Sample (material); Computer science; Arithmetic; Mathematics; Linguistics; Data mining; Philosophy; Sociology; Population; Demography","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":[],"consensus_categories":[],"category_scores_codex":[0.001482724,0.0004323722,0.0003961078,0.00262843,0.0008129082,0.003967677,0.0007381601,0.0008267869,0.07669363],"category_scores_gemma":[0.009371588,0.0003133815,0.0004135599,0.004358376,0.0008174463,0.0044889,0.001122999,0.001619512,0.02250386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001354371,"about_ca_system_score_gemma":0.001774155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002853367,"about_ca_topic_score_gemma":0.001861267,"domain_scores_codex":[0.9988747,0.0004204428,0.0001032102,0.0001665571,0.0003634582,0.00007160644],"domain_scores_gemma":[0.9975932,0.001225117,0.0001562779,0.0003837203,0.0005036367,0.0001380582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002372802,0.00001501484,0.001154019,0.00009801657,0.000006544375,0.00003516486,0.0001974994,0.001168061,0.0001063072,0.7233255,0.1553771,0.1184931],"study_design_scores_gemma":[0.000005605263,0.00001363998,0.0009980843,0.0001754229,0.000004195891,0.0001311469,0.0001559139,0.0009270046,0.0001071469,0.2031987,0.7942673,0.00001575126],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008309786,0.01010837,0.247709,0.01282862,0.002019992,0.0005553547,0.06506348,0.002085876,0.6513196],"genre_scores_gemma":[0.1983867,0.02342287,0.3603664,0.00698271,0.002454412,0.001810536,0.08526689,0.001772635,0.3195369],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07669363,"threshold_uncertainty_score":0.2565657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01156674245623877,"score_gpt":0.2830971458336958,"score_spread":0.271530403377457,"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."}}