{"id":"W4402923446","doi":"10.3390/jrfm17100431","title":"Explainable Machine Learning for Fallout Prediction in the Mortgage Pipeline","year":2024,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Computer science; Machine learning; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001658008,0.0006046685,0.0005293443,0.001246421,0.0003844139,0.0005801821,0.0005165383,0.0006738353,0.001101348],"category_scores_gemma":[0.005615178,0.0002222114,0.0005127281,0.0008958926,0.0003036648,0.0009503139,0.0004938083,0.001065575,0.0002423973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005720276,"about_ca_system_score_gemma":0.0006731412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01200164,"about_ca_topic_score_gemma":0.01021953,"domain_scores_codex":[0.9997223,0.0001126113,0.00001918912,0.000066582,0.00003157761,0.00004772845],"domain_scores_gemma":[0.9977612,0.001683866,0.0002262967,0.0001073179,0.0001570366,0.00006424568],"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":[0.0001870611,0.000374517,0.06559934,0.000063587,0.0001211868,0.0001639793,0.0001643827,0.8100083,0.000915779,0.003849081,0.002222362,0.1163304],"study_design_scores_gemma":[0.00000272442,0.00001432792,0.002231225,0.000003548786,0.000003526015,0.000006770081,0.00001490415,0.9954306,0.00007501431,0.002096249,0.0001185223,0.00000262796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6769726,0.001145427,0.3170548,0.001283745,0.00006871593,0.00007512049,0.0009798226,0.0009611934,0.0014586],"genre_scores_gemma":[0.978085,0.0002093867,0.02009965,0.00004117288,0.00004386339,0.00004118619,0.0007758409,0.00001750425,0.0006864389],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01200164,"threshold_uncertainty_score":0.02386355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005550790625841798,"score_gpt":0.2021827765220774,"score_spread":0.1966319858962357,"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."}}