{"id":"W4247095889","doi":"10.1093/geront/gnv622.05","title":"ENHANCING THE EMPIRICAL UNDERSTANDING OF FINANCIAL EXPLOITATION","year":2015,"lang":"en","type":"article","venue":"The Gerontologist","topic":"Business and Economic Development","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Finance; Empirical research; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005809544,0.00005109529,0.00007458644,0.000005070836,0.0001116927,0.00001250534,0.0001800909,0.00002462323,0.0001835693],"category_scores_gemma":[0.00009672595,0.00002662412,0.00001873215,0.0000605396,0.00026637,0.00007541142,0.00009736193,0.00004627172,0.0001034114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002422469,"about_ca_system_score_gemma":0.00002429905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003732163,"about_ca_topic_score_gemma":0.001414106,"domain_scores_codex":[0.9995117,0.00003351469,0.0001466811,0.00009029551,0.00009567433,0.0001221392],"domain_scores_gemma":[0.9997059,0.00006050862,0.00007073425,0.0001353391,0.000003655259,0.00002382307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005879339,0.0003946158,0.4510534,0.00004538031,0.00007919506,0.00001850013,0.1465482,0.01839215,0.00466925,0.03735645,0.2760538,0.06480109],"study_design_scores_gemma":[0.0010071,0.0001376215,0.8839954,0.00002759408,0.00003451788,0.00002490013,0.02527521,0.001835066,0.003551807,0.0577019,0.0259946,0.0004142603],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609551,0.00004190953,0.01782348,0.003654812,0.0003120951,0.0001063946,6.589991e-7,0.00001389817,0.01709159],"genre_scores_gemma":[0.9990583,0.000003725763,0.0003744582,0.0002779243,0.00002432844,0.000008613206,6.312426e-7,0.000002690751,0.0002493009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.432942,"threshold_uncertainty_score":0.2009955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2783191275616942,"score_gpt":0.3033425073503938,"score_spread":0.02502337978869956,"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."}}