{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":1,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":1,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"2e244396a65d","filters":{"venue":"International Journal of Automation Artificial Intelligence and Machine Learning"}},"results":[{"id":"W4390274018","doi":"10.61797/ijaaiml.v3i1.275","title":"Financial Risk Assessment using Machine Learning Engineering (FRAME): Scenario based Quantitative Analysis under Uncertainty","year":2023,"lang":"en","type":"article","venue":"International Journal of Automation Artificial Intelligence and Machine Learning","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Abstraction; Computer science; Artificial intelligence; Excellence; Risk management; Machine learning; Risk analysis (engineering); Risk assessment; Financial engineering; Frame (networking); Quantitative analysis (chemistry); Financial risk; Granularity; Finance; Business; Computer security","authors":[{"name":"Krishna Mohan Kovur","is_ca":true},{"name":"Medha Gedela","is_ca":false},{"name":"Arjun M. Rao","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0411206315140044,"gpt":0.309395370095649,"spread":0.2682747385816446,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001185366,0.0001989576,0.0003044211,0.00142306,0.0003490863,0.0005154738,0.0002267378,0.00008704943,0.0001766387],"category_scores_gemma":[0.001213341,0.0001874563,0.0002142979,0.001175189,0.00004882532,0.001017594,0.000102325,0.0006509256,0.00002692926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001172576,"about_ca_system_score_gemma":0.00007685283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001879579,"about_ca_topic_score_gemma":0.0003840099,"domain_scores_codex":[0.9981158,0.00006469789,0.000753444,0.0002266661,0.0006179344,0.0002214314],"domain_scores_gemma":[0.9980462,0.0001922184,0.0009940851,0.00006921966,0.0006737745,0.00002456385],"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":[0.00009154149,0.00005202349,0.03595456,0.00002044292,0.0001824753,0.00002142144,0.0001135745,0.9340037,0.0009656207,0.01401343,0.0000101107,0.01457116],"study_design_scores_gemma":[0.0001284446,0.00005305389,0.04259833,0.00009355426,0.0002530319,0.000003809648,0.0002812181,0.9526826,0.00009158273,0.002469689,0.001166967,0.0001777267],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5756425,0.00005467836,0.4227817,0.0005453291,0.0007238582,0.00007062331,0.00001183406,0.0001186462,0.00005080058],"genre_scores_gemma":[0.9965808,0.00007723493,0.002379515,0.0001540989,0.0006031368,0.000003023893,0.0001643351,0.00001993613,0.00001792839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4209383,"threshold_uncertainty_score":0.7644245,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}