{"id":"W2127737754","doi":"10.25336/p6vs46","title":"Support Vector Machines as tools for mortality graduation","year":2012,"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":"Graduation (instrument); Support vector machine; Nonparametric statistics; Parametric statistics; Computer science; Variety (cybernetics); Machine learning; Statistics; Econometrics; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.007517676,0.0009219522,0.0009888079,0.005380011,0.0003818745,0.002099665,0.001267316,0.00113848,0.002423136],"category_scores_gemma":[0.03701124,0.0003034672,0.0005704508,0.003573914,0.0009379047,0.002282534,0.001779126,0.001988779,0.0009158301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006852151,"about_ca_system_score_gemma":0.0007349072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001189847,"about_ca_topic_score_gemma":0.0008401358,"domain_scores_codex":[0.9944951,0.003035793,0.0004409906,0.0003732498,0.001497115,0.0001576974],"domain_scores_gemma":[0.9824795,0.01272261,0.001498637,0.000920612,0.001965489,0.000413104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000154901,0.0001929888,0.0133922,0.0003674123,0.0001466817,0.0001433831,0.0005772879,0.1210542,0.0009339661,0.0687725,0.009612693,0.7846517],"study_design_scores_gemma":[0.00003727774,0.000209725,0.007313029,0.000273563,0.00003850878,0.0001984889,0.0004251433,0.8186372,0.002214269,0.1531876,0.01736651,0.00009867766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0311492,0.00585822,0.9536216,0.001277341,0.0002527237,0.000122195,0.0004180443,0.002357171,0.00494355],"genre_scores_gemma":[0.4814554,0.002772914,0.5101869,0.0002097641,0.0004842646,0.0002728061,0.0008061518,0.0001864703,0.003625325],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007517676,"threshold_uncertainty_score":0.03975779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1680766289117301,"score_gpt":0.4362057539197982,"score_spread":0.268129125008068,"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."}}