{"id":"W2914623390","doi":"10.3390/jrfm12010030","title":"Predicting Micro-Enterprise Failures Using Data Mining Techniques","year":2019,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Profitability index; Equity (law); Logistic regression; Financial ratio; Gradient boosting; Equity capital; Econometrics; Computer science; Business; Finance; Capital market; Machine learning; Economics; Random forest","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":[0.001601953,0.0006651494,0.0007048781,0.004580895,0.0003224218,0.001069137,0.0006515529,0.0005358147,0.0008111105],"category_scores_gemma":[0.006083655,0.0002098179,0.0007229001,0.002863562,0.000185799,0.0009604737,0.0005188761,0.0005484573,0.0004518847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003929139,"about_ca_system_score_gemma":0.0005029155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003782838,"about_ca_topic_score_gemma":0.003892532,"domain_scores_codex":[0.9991616,0.0002333017,0.0001460324,0.000147833,0.0002397703,0.00007152693],"domain_scores_gemma":[0.9944704,0.00371979,0.0007060661,0.0003173258,0.0005928224,0.0001935313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003012446,0.0007028505,0.6173185,0.0003789196,0.0004527842,0.0007954472,0.0004608661,0.1109002,0.002508329,0.001211627,0.002785366,0.2621838],"study_design_scores_gemma":[0.00003501262,0.0005034769,0.2347607,0.0001912324,0.0001740722,0.0005532788,0.001382155,0.7457709,0.004264337,0.007197534,0.00510987,0.00005742144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9203776,0.001047681,0.07068393,0.0005549652,0.00004518522,0.0003283042,0.004139866,0.0005638872,0.002258654],"genre_scores_gemma":[0.9687412,0.0004329134,0.02737516,0.00002939485,0.00002338583,0.0001421245,0.002722757,0.00001118724,0.0005217917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004580895,"threshold_uncertainty_score":0.008472025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215401104728619,"score_gpt":0.2223708633434211,"score_spread":0.2102168522961349,"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."}}