{"id":"W4360608960","doi":"10.21203/rs.3.rs-2709173/v1","title":"Financial Exploitation in Canada: A Predictive Model using ML and AI","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Roads University","funders":"","keywords":"Business; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00358093,0.001295052,0.001027462,0.00253179,0.002118744,0.003063599,0.002302377,0.001024592,0.004961249],"category_scores_gemma":[0.007850911,0.0005011026,0.001243427,0.002142972,0.001068412,0.0007449622,0.001222386,0.002552917,0.0006534082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01445,"about_ca_system_score_gemma":0.01508202,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9257447,"about_ca_topic_score_gemma":0.822522,"domain_scores_codex":[0.9992182,0.0002679744,0.00003766457,0.0001499242,0.0001292794,0.0001969213],"domain_scores_gemma":[0.9949064,0.002856177,0.0002277661,0.0001200386,0.001596122,0.0002935662],"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":[0.000886357,0.0007170644,0.3393735,0.0002809026,0.0006543672,0.0007537455,0.0005502755,0.5773538,0.0002527804,0.007572389,0.0148387,0.05676601],"study_design_scores_gemma":[0.00003425376,0.00004335113,0.01640351,0.00005369671,0.0001000752,0.00002727003,0.0002797627,0.9802462,0.00005908796,0.001248481,0.001479677,0.00002466185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9481022,0.00246153,0.02416426,0.006241777,0.000298781,0.0003465646,0.007011277,0.0006845429,0.01068902],"genre_scores_gemma":[0.983192,0.0008161576,0.007755808,0.0002044338,0.00005945676,0.0001106623,0.003214173,0.00002892727,0.004618387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07425529,"threshold_uncertainty_score":0.1493852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1538454706743684,"score_gpt":0.3385161803548801,"score_spread":0.1846707096805117,"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."}}