{"id":"W6979365818","doi":"","title":"A Population Sampling Framework for Claim Reserving in General Insurance","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weighting; Sampling (signal processing); Aggregate (composite); Population; Sampling bias; Sampling design; Inverse probability weighting","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":[0.01643915,0.0009200952,0.00125621,0.001961944,0.0008051746,0.002216915,0.004099448,0.002018324,0.005543705],"category_scores_gemma":[0.03198425,0.0007581489,0.001502384,0.002027871,0.002643909,0.003464609,0.002297109,0.002524844,0.0005598433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002284259,"about_ca_system_score_gemma":0.001530137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01458759,"about_ca_topic_score_gemma":0.009988968,"domain_scores_codex":[0.9936655,0.00445017,0.000170585,0.0008599428,0.0006487296,0.000205085],"domain_scores_gemma":[0.9851543,0.01139494,0.001158633,0.001187868,0.0008164513,0.0002877512],"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":[0.00003893673,0.00005430917,0.005159524,0.0000970799,0.00008753033,0.0002327931,0.000549475,0.1687603,0.0002961276,0.8014538,0.001369907,0.02190028],"study_design_scores_gemma":[0.00002532027,0.00005771752,0.001153533,0.0000422533,0.00003173463,0.0001044824,0.0001169139,0.7307976,0.0001251951,0.2651679,0.00235012,0.00002729905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01137526,0.000366518,0.9854656,0.000627363,0.00004278689,0.00009938094,0.0002027188,0.00008956948,0.001730597],"genre_scores_gemma":[0.5607486,0.001645049,0.4258661,0.0005383383,0.0003488871,0.000952079,0.001010701,0.0001213204,0.00876901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01643915,"threshold_uncertainty_score":0.08693957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3016369360652444,"score_gpt":0.4707470434177993,"score_spread":0.1691101073525549,"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."}}