{"id":"W4388994252","doi":"10.1145/3604237.3626849","title":"The complexity of financial wellness: examining survey patterns via kernel metric learning and clustering of mixed-type data","year":2023,"lang":"en","type":"article","venue":"","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Universitas Brawijaya","keywords":"Cluster analysis; Kernel (algebra); Metric (unit); Computer science; Artificial intelligence; Mathematics; Business; Marketing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006672526,0.0001109128,0.0002525395,0.0001969985,0.0006056061,0.00006286369,0.0006828976,0.00005836157,0.00003718583],"category_scores_gemma":[0.001191934,0.00009132871,0.00003332017,0.001754358,0.0006733876,0.0001772904,0.0008242899,0.0001405699,0.000006371631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001617687,"about_ca_system_score_gemma":0.00004785056,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03338754,"about_ca_topic_score_gemma":0.09395787,"domain_scores_codex":[0.9976761,0.0007611572,0.0003841293,0.0003075887,0.0005362534,0.0003348145],"domain_scores_gemma":[0.9984133,0.0007764972,0.000244291,0.000394085,0.0001221889,0.00004961655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001652863,0.00001987783,0.9660498,0.00005907829,0.00003531257,0.000001840509,0.0009616461,0.00007800304,0.0000129148,0.001677759,0.0003037025,0.03078352],"study_design_scores_gemma":[0.0001388914,0.00003504477,0.9914614,0.00002048457,0.00001833395,1.187684e-7,0.00254931,0.003523538,0.00002633322,0.0003652769,0.001751406,0.0001098708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923724,0.0001562586,0.003365617,0.00007927466,0.0006326473,0.0002487761,0.00004503031,0.00007918011,0.003020798],"genre_scores_gemma":[0.998547,0.0008650647,0.0001316865,0.00001186869,0.00005735867,0.000003035483,0.00004938621,0.00001094326,0.0003236649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06057033,"threshold_uncertainty_score":0.9730492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1501361742118885,"score_gpt":0.3505963864181768,"score_spread":0.2004602122062882,"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."}}