{"id":"W2012284576","doi":"10.5539/ass.v8n8p155","title":"The Construction of Indicator System for Performance Measurement of Chinese Enterprises Based on Balanced Scorecard","year":2012,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Evaluation and Optimization Models","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Balanced scorecard; Business; Construct (python library); China; Face (sociological concept); Performance measurement; Perspective (graphical); Set (abstract data type); Chinese economy; Process management; Accounting; Industrial organization; Risk analysis (engineering); Computer science; Marketing","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":[0.0008098037,0.00004603128,0.00007412851,0.00004611993,0.0001740029,0.000009975087,0.0001185799,0.00001954895,0.000003175721],"category_scores_gemma":[0.00005542597,0.00003313422,0.00002903822,0.0002349003,0.0001726798,0.000118076,0.000005703624,0.00002442765,0.000001109625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001053053,"about_ca_system_score_gemma":0.00006019855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.715822e-7,"about_ca_topic_score_gemma":3.031375e-7,"domain_scores_codex":[0.9992459,0.0000150682,0.000145795,0.00005337529,0.0004186909,0.0001211973],"domain_scores_gemma":[0.9996742,0.0000198853,0.00007563375,0.00007204105,0.0001267048,0.00003154676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003042025,0.0002293641,0.319185,0.00147471,0.0001015692,6.251796e-8,0.01574249,0.1087226,0.06241199,0.04315864,0.0004232319,0.4482462],"study_design_scores_gemma":[0.001075053,0.0001067055,0.4042888,0.0001492353,0.00002607942,6.864705e-7,0.001365766,0.528612,0.06381848,0.0000704029,0.0002521482,0.0002347119],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6216146,0.0001084887,0.2862,0.0002220376,0.002350795,0.001093093,0.00003264927,0.0001655822,0.08821283],"genre_scores_gemma":[0.9985207,0.000003149445,0.001397193,0.000006961798,0.00004602561,0.00002000326,6.740258e-7,0.000003927868,0.000001407242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4480115,"threshold_uncertainty_score":0.1351174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01807320535535973,"score_gpt":0.2566821170943977,"score_spread":0.238608911739038,"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."}}