{"id":"W2552541708","doi":"","title":"Higher-Order Feature Synthesis for Insurance Scoring Models","year":2009,"lang":"en","type":"article","venue":"","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Overfitting; Feature selection; Profitability index; Computer science; Sorting; Feature (linguistics); Rank (graph theory); Data mining; Selection (genetic algorithm); Knapsack problem; Ranking (information retrieval); Heuristics; Order (exchange); Machine learning; Mathematics; Algorithm; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.005086126,0.00113236,0.001698889,0.001467121,0.0005722506,0.001566787,0.001189619,0.001281837,0.004881994],"category_scores_gemma":[0.01283684,0.0005622743,0.001889633,0.00127573,0.0005754555,0.001556972,0.001058533,0.002225569,0.001204819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001012057,"about_ca_system_score_gemma":0.001116639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005077748,"about_ca_topic_score_gemma":0.004787064,"domain_scores_codex":[0.9982485,0.0008993493,0.0001230511,0.0002718042,0.0002853582,0.0001719497],"domain_scores_gemma":[0.9925717,0.005862487,0.0003915705,0.0005337597,0.0005296797,0.0001108665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001928951,0.0001712097,0.002626377,0.0001008063,0.0001152166,0.0001424471,0.0001077127,0.825429,0.001759845,0.01362718,0.002016381,0.153711],"study_design_scores_gemma":[0.000007370061,0.00002715982,0.0002730167,0.000005469109,0.000007072114,0.00001032672,0.000004854701,0.9923402,0.0001866883,0.006938474,0.0001925395,0.000006805663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03047156,0.0002215769,0.9672026,0.0002543718,0.00002165997,0.0000833345,0.0003014558,0.0008966542,0.000546796],"genre_scores_gemma":[0.7332974,0.0002711393,0.2592816,0.0002109807,0.0001020697,0.0007210265,0.001992034,0.000172414,0.003951304],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005086126,"threshold_uncertainty_score":0.02689832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03648465261786496,"score_gpt":0.2216666002682066,"score_spread":0.1851819476503417,"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."}}