{"id":"W3126525290","doi":"10.3390/jrfm14020067","title":"Modeling Study on Risk Identification in the Process of Anti-Crisis Enterprise Management","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Economic and Business Development Strategies","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Process (computing); Computer science; Risk analysis (engineering); Fuzzy logic; Risk management; Crisis management; Task (project management); Sample (material); Process management; Management science; Business; Artificial intelligence; Engineering; Systems engineering; Economics; Management","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001271228,0.0001134997,0.0003340038,0.0003474587,0.00008953517,0.00008007039,0.0002188375,0.00003086323,0.000009974362],"category_scores_gemma":[0.00003595422,0.00009803724,0.00007554689,0.0003018126,0.00001660127,0.0002011751,0.00005689303,0.0001572032,0.000007189594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003528419,"about_ca_system_score_gemma":0.00001123985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004047099,"about_ca_topic_score_gemma":0.00002111006,"domain_scores_codex":[0.9985702,0.00003665995,0.0009678853,0.0002178858,0.00007813614,0.0001292278],"domain_scores_gemma":[0.9990309,0.00002125737,0.000686089,0.0001884888,0.0000542723,0.00001902597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000202573,0.002320012,0.8538701,0.0003480649,0.000261944,0.0002361295,0.01408133,0.025022,0.000001232746,0.07006528,0.000290547,0.03330076],"study_design_scores_gemma":[0.001407575,0.0000929147,0.9313172,0.00008387991,0.00007824734,0.00000427255,0.02409636,0.001388435,0.00001028846,0.04047608,0.000882366,0.0001623366],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759361,0.0006828406,0.02149146,0.0001166493,0.0002632326,0.0002210146,0.00001457522,0.000002560353,0.001271564],"genre_scores_gemma":[0.9921554,0.007408096,0.0002889218,0.00005529067,0.00004250624,0.00001154204,0.000001656772,0.000006853036,0.0000297837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07744712,"threshold_uncertainty_score":0.3997843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01976063831648377,"score_gpt":0.2303517491489316,"score_spread":0.2105911108324478,"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."}}