{"id":"W1816679487","doi":"10.25336/p65w28","title":"The Probabilistic Life Table and Its Applications to Canada","year":2015,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Probabilistic logic; Statistics; Life table; Sample (material); Variable (mathematics); Mathematics; Econometrics; Population; Demography; Computer science; Data mining; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004897609,0.0004180988,0.000496495,0.002886567,0.002304797,0.001876117,0.00164337,0.0006967325,0.01020747],"category_scores_gemma":[0.02702332,0.0003757697,0.001006383,0.005595189,0.001524492,0.001284224,0.001413581,0.001372397,0.0006249683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02281893,"about_ca_system_score_gemma":0.03330997,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9027215,"about_ca_topic_score_gemma":0.8606642,"domain_scores_codex":[0.997724,0.000833633,0.0001010847,0.0002430332,0.0009326636,0.0001654844],"domain_scores_gemma":[0.989823,0.004630894,0.0004727141,0.0006790763,0.004082015,0.0003124616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0000737638,0.00002747654,0.01293151,0.0001773681,0.00007169519,0.0003103985,0.000684165,0.1232871,0.0001425469,0.6873943,0.02956154,0.1453382],"study_design_scores_gemma":[0.0000490585,0.00003525244,0.01330941,0.0002330621,0.00006167308,0.0003788361,0.0005296832,0.3892716,0.0003455303,0.4519331,0.1437168,0.0001360593],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02797153,0.005967632,0.8424537,0.0106708,0.0005764201,0.0005551493,0.01132839,0.001608559,0.09886774],"genre_scores_gemma":[0.4122578,0.00691847,0.5569267,0.0008364072,0.0002471789,0.0004827501,0.003882635,0.0003835076,0.01806461],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09727854,"threshold_uncertainty_score":0.1957028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08491613987052238,"score_gpt":0.3518152688200497,"score_spread":0.2668991289495273,"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."}}