{"id":"W7132102467","doi":"","title":"吉利全球化:中国企业出海启示录","year":2025,"lang":"","type":"article","venue":"CEIBS Institutional Repository","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Casa","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004492883,0.0004919225,0.0003360547,0.002414808,0.006328727,0.01673131,0.001014935,0.003430929,0.01431381],"category_scores_gemma":[0.007091259,0.0003229993,0.0003938774,0.002985857,0.01748864,0.01158848,0.002630349,0.002860744,0.002059238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01176515,"about_ca_system_score_gemma":0.01931566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01977892,"about_ca_topic_score_gemma":0.02017982,"domain_scores_codex":[0.9966132,0.0015721,0.00014044,0.0004234331,0.00088539,0.0003654767],"domain_scores_gemma":[0.9969665,0.001504873,0.0002745995,0.0001915931,0.0007329541,0.0003293968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007754299,0.00002109325,0.0004783016,0.00003872449,0.00000395303,0.00003344726,0.006081352,0.0001912884,0.00007009239,0.9770097,0.006614952,0.009449343],"study_design_scores_gemma":[0.00002031163,0.00002746909,0.001895644,0.0002600579,0.0000153297,0.00008293388,0.02240612,0.0005945198,0.0004694189,0.7665539,0.2076461,0.00002807195],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03495262,0.004795876,0.009162644,0.07492292,0.0009223369,0.00009486583,0.0002181316,0.0001006553,0.8748299],"genre_scores_gemma":[0.8991854,0.003005496,0.007405241,0.004985976,0.0005638487,0.0002432275,0.0001117529,0.00006561287,0.08443351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01977892,"threshold_uncertainty_score":0.08536255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00601936839126198,"score_gpt":0.2112424394399227,"score_spread":0.2052230710486607,"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."}}