{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008227298,0.0001987505,0.0006374163,0.0002740551,0.0004864716,0.000190969,0.0003325122,0.00007282884,0.00001589868],"category_scores_gemma":[0.0008648896,0.0001860099,0.000118303,0.00004711426,0.0001793598,0.001406826,0.0001516943,0.0001910908,0.000001571515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001658489,"about_ca_system_score_gemma":0.000223515,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05360274,"about_ca_topic_score_gemma":0.1294323,"domain_scores_codex":[0.9985874,0.00001255171,0.0007050596,0.000214597,0.0001007228,0.000379614],"domain_scores_gemma":[0.9983779,0.00002820667,0.001198023,0.0001832106,0.0001688131,0.00004380253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001391407,0.0003608626,0.3986191,0.0009688862,0.0001448391,0.0002450235,0.0006199399,0.001165078,0.00002940787,0.008825331,0.009124077,0.5785061],"study_design_scores_gemma":[0.003701495,0.0001329477,0.9639187,0.0006455727,0.0001573007,0.0000339549,0.0004566406,0.01316461,0.00002500645,0.007723628,0.009532696,0.0005074049],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885976,0.0008771066,0.00002655914,0.0003472341,0.0009705414,0.00006309499,0.00003973401,0.000005313846,0.009072759],"genre_scores_gemma":[0.9971321,0.000688343,0.0003063427,0.00007377706,0.001725106,0.00000773688,0.000005631066,0.00001535016,0.00004564064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5779987,"threshold_uncertainty_score":0.9526994,"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."}}