{"id":"W4409798084","doi":"10.61091/jcmcc127b-366","title":"Comprehensive assessment model and method of international trade market competitiveness based on principal component analysis","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Suzhou Vocational University","keywords":"Principal component analysis; Component (thermodynamics); International trade; Principal (computer security); Business; Industrial organization; Economics; Computer science; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001266593,0.0003173807,0.001061395,0.0007737604,0.000196207,0.0002647373,0.000434819,0.0001189924,0.00001698647],"category_scores_gemma":[0.0001126301,0.0002908319,0.0002978195,0.0007269186,0.0001113035,0.0002499976,0.0002992695,0.0003575083,2.272317e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008377853,"about_ca_system_score_gemma":0.0001124645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002228236,"about_ca_topic_score_gemma":7.030835e-7,"domain_scores_codex":[0.997588,0.000090339,0.001062083,0.0002802677,0.0007388357,0.0002405032],"domain_scores_gemma":[0.9973189,0.0008046462,0.001171134,0.0002099915,0.000450556,0.00004479228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003116231,0.001018067,0.01014471,0.0005866787,0.0007662746,0.00001446718,0.00006040979,0.01270219,0.0003522556,0.9733415,0.00003588759,0.0006658916],"study_design_scores_gemma":[0.005373154,0.0001436759,0.03880353,0.0006956244,0.0009652234,0.000006737942,0.0003375688,0.8376163,0.0001220952,0.1131945,0.00243242,0.000309201],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7736272,0.0001860426,0.1876142,0.001721795,0.01137502,0.0006913173,0.00002074666,0.00006375014,0.02469993],"genre_scores_gemma":[0.9895181,0.00001655035,0.009794336,0.0002247888,0.0004162752,0.000002552601,0.000006223978,0.0000169436,0.000004233721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8601471,"threshold_uncertainty_score":0.9999544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01638738696164348,"score_gpt":0.2842518854366499,"score_spread":0.2678644984750064,"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."}}