{"id":"W3200121749","doi":"10.1108/gs-03-2021-0041","title":"A hybrid predictive framework for evaluating P2P credit risks","year":2021,"lang":"en","type":"article","venue":"Grey Systems Theory and Application","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Data mining; Randomness; Support vector machine; Machine learning; Feature selection; Flexibility (engineering); Key (lock); Artificial intelligence; Selection (genetic algorithm); Representativeness heuristic; Cluster analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002801132,0.0009732938,0.0009186346,0.001913974,0.0004710563,0.001672441,0.001569282,0.0009546957,0.001036932],"category_scores_gemma":[0.006193629,0.0003059061,0.0007241147,0.001462664,0.0009288268,0.001733232,0.001085261,0.0009854824,0.0001573206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001312109,"about_ca_system_score_gemma":0.001090944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009594616,"about_ca_topic_score_gemma":0.00560934,"domain_scores_codex":[0.998847,0.0003906021,0.00006241486,0.0002505021,0.0003531096,0.00009625826],"domain_scores_gemma":[0.9980174,0.001163143,0.000227356,0.00009016971,0.0004253375,0.00007654246],"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":[0.00004058184,0.00004582555,0.003817611,0.00004286955,0.00005985254,0.00008277984,0.00006531709,0.9458266,0.0006790566,0.01059726,0.0005645146,0.03817767],"study_design_scores_gemma":[9.798628e-7,0.000007095524,0.0002123615,0.000002613501,0.000004192349,0.000005950721,0.000006225041,0.9977961,0.00007621448,0.001814856,0.00007118288,0.000002404769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04454868,0.0004163361,0.9524461,0.0003392645,0.00003086659,0.00007174726,0.0001476637,0.0002644026,0.001734884],"genre_scores_gemma":[0.9194569,0.0002798984,0.07883461,0.00008053566,0.00006544107,0.0001408387,0.0002083566,0.00002337175,0.0009099692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009594616,"threshold_uncertainty_score":0.01907754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02991703235716341,"score_gpt":0.2924527461511255,"score_spread":0.2625357137939621,"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."}}