{"id":"W7112040612","doi":"","title":"РОЗРАХУНОК ФУНКЦІЇ ЧИСЕЛЬНОСТІ НАСЕЛЕННЯ ДЛЯ ДИНАМІЧНОЇ МОДЕЛІ З НЕПЕРЕРВНИМ ЧАСОМ","year":2008,"lang":"en","type":"article","venue":"The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Identification (biology); Process (computing); Function (biology); Term (time)","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":[0.001224669,0.0003393226,0.0003967376,0.001651757,0.000875766,0.002598068,0.000472662,0.0006137596,0.009757547],"category_scores_gemma":[0.003152873,0.000505858,0.0004565197,0.001696155,0.001355143,0.001528647,0.00103594,0.001024915,0.003921033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052376,"about_ca_system_score_gemma":0.002212382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004251112,"about_ca_topic_score_gemma":0.004037265,"domain_scores_codex":[0.9989493,0.0001942434,0.00006559445,0.0002095051,0.0004607137,0.0001205917],"domain_scores_gemma":[0.9989943,0.0002679013,0.0001257736,0.0001741929,0.0003774409,0.00006050088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001179456,0.00006312629,0.007780763,0.0004790997,0.00006171933,0.001131782,0.003493258,0.0112648,0.01826023,0.5650672,0.00595194,0.3863281],"study_design_scores_gemma":[0.00004787568,0.0002630066,0.01686335,0.0003991995,0.000188902,0.003936787,0.003635146,0.02794882,0.0279984,0.3871129,0.5313632,0.0002423667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1029737,0.00962413,0.6738931,0.002586302,0.0008284848,0.0001716268,0.0007311095,0.0004604696,0.2087311],"genre_scores_gemma":[0.7273904,0.008562382,0.2108963,0.0001371807,0.0003078092,0.0002763959,0.0003671116,0.0002605672,0.05180182],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009757547,"threshold_uncertainty_score":0.03264225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1122434134709307,"score_gpt":0.3674910940156276,"score_spread":0.2552476805446969,"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."}}