{"id":"W2725855344","doi":"10.18533/jefs.v5i3.272","title":"Likelihood of financial distress in Canadian oil and gas market: An optimized hybrid forecasting approach","year":2017,"lang":"en","type":"article","venue":"Journal of Economic & Financial Studies","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Financial distress; Business; Economics; Econometrics; Petroleum engineering; Financial system; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001122552,0.0004707268,0.000395319,0.001031678,0.0002966096,0.0008179437,0.0008081525,0.0004222979,0.0008822528],"category_scores_gemma":[0.002790967,0.0002501314,0.0004433947,0.0008114966,0.0002457572,0.0005741378,0.0004130571,0.0004775271,0.00007417959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002183932,"about_ca_system_score_gemma":0.002152861,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3339478,"about_ca_topic_score_gemma":0.2798291,"domain_scores_codex":[0.999754,0.0000708424,0.00001303409,0.00005106393,0.00006269194,0.00004837805],"domain_scores_gemma":[0.9992873,0.0003448632,0.00009648123,0.00003516208,0.0001965004,0.00003962358],"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":[0.00008377257,0.00002668429,0.01849243,0.00001751805,0.00006465951,0.00005105505,0.00004312917,0.9478728,0.0004164368,0.002368555,0.0005422629,0.03002063],"study_design_scores_gemma":[0.000001896424,0.000005420853,0.003011975,0.000001587001,0.000007646116,0.000003835699,0.00001089861,0.9964513,0.00006509986,0.0003814538,0.00005354815,0.000005393986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8457218,0.000457021,0.1464538,0.001086851,0.00003163925,0.00005948369,0.0007671997,0.000315421,0.005106781],"genre_scores_gemma":[0.9898673,0.00008569323,0.008952355,0.00002055639,0.00001064476,0.00001030001,0.0002379002,0.000006332295,0.0008089171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6660522,"threshold_uncertainty_score":0.664008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02921808491004295,"score_gpt":0.2360786407313595,"score_spread":0.2068605558213166,"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."}}