{"id":"W2775366074","doi":"10.5430/ijfr.v9n1p41","title":"Performance Evaluation and Determinant Factors of China’s Logistics Enterprises Based on Careersmart Balanced Score Card","year":2017,"lang":"en","type":"article","venue":"International Journal of Financial Research","topic":"Outsourcing and Supply Chain Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; China; Index (typography); Human capital; Empirical research; Liability; Scale (ratio); Asset (computer security); Service (business); Investment (military); Marketing; Industrial organization; Finance; Economics; Economic growth","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":[0.00119636,0.0002515242,0.0001396861,0.002123683,0.0005334619,0.0007106683,0.0002088026,0.0001622796,0.001879214],"category_scores_gemma":[0.002172403,0.00007983942,0.0002523354,0.002016634,0.0003289896,0.0004241028,0.0006678747,0.0002084408,0.0002970049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000787997,"about_ca_system_score_gemma":0.00132001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01561659,"about_ca_topic_score_gemma":0.01972757,"domain_scores_codex":[0.9994146,0.0000917088,0.00006584417,0.00005824053,0.0002129781,0.0001566521],"domain_scores_gemma":[0.9970469,0.0003667779,0.0009131297,0.0001448344,0.0007937404,0.0007345696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001402075,0.00002629491,0.9965324,0.000003283102,0.00000539389,0.00002760214,0.000110151,0.0001510519,0.00008826117,0.00007689816,0.0001370049,0.002827674],"study_design_scores_gemma":[0.000001384286,0.00003306385,0.9984753,0.000003527015,0.000003046982,0.00001040161,0.0003082432,0.0008451624,0.00009604191,0.00002693553,0.000194523,0.00000246908],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987469,0.00001324625,0.00005366906,0.00002784014,0.000001244045,0.000006058973,0.0001490779,0.000001423082,0.001000631],"genre_scores_gemma":[0.9992495,0.00001605471,0.00006285368,0.000003538827,0.000001497241,0.000003854645,0.0003580399,3.793782e-7,0.0003041753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01561659,"threshold_uncertainty_score":0.0310514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0867258101039737,"score_gpt":0.3622068960669605,"score_spread":0.2754810859629868,"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."}}