{"id":"W2035191842","doi":"10.1007/s11192-006-0133-x","title":"Comparing business competition positions based on Web co-link data: The global market vs. the Chinese market","year":2006,"lang":"en","type":"article","venue":"Scientometrics","topic":"Web visibility and informetrics","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Multidimensional scaling; Competition (biology); Similarity (geometry); Business; Competitive advantage; Link (geometry); Web site; Market share; Industrial organization; Marketing; Computer science; The Internet; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.005143519,0.0002542378,0.000238723,0.001445927,0.001124578,0.001686889,0.004861056,0.00008810701,0.00008963929],"category_scores_gemma":[0.001677514,0.0001492452,0.00009569216,0.04925736,0.0003507506,0.001232179,0.0009241946,0.0003106436,0.0001003236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003140129,"about_ca_system_score_gemma":0.0003097867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002077989,"about_ca_topic_score_gemma":0.0001266101,"domain_scores_codex":[0.9961457,0.0002414302,0.0004741487,0.0006806065,0.001893774,0.0005642959],"domain_scores_gemma":[0.9950925,0.001313894,0.000226017,0.002721716,0.0005190619,0.0001268182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001482008,0.001440352,0.5438882,0.0001333397,0.00004291904,0.00002474909,0.00009040601,0.01937346,0.00002094004,0.1051034,0.3074465,0.02228748],"study_design_scores_gemma":[0.0003146132,0.00003400122,0.4882874,0.00001351305,0.000007377316,0.000007970184,0.000006744972,0.4847694,0.000004076539,0.0006825743,0.02574037,0.0001318945],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04637431,0.0002796288,0.6097994,0.01797105,0.00327514,0.001012933,0.0007309603,0.000450414,0.3201061],"genre_scores_gemma":[0.9929336,0.00002036455,0.00432794,0.00195857,0.000275738,0.00001073215,0.0001720753,0.000008337264,0.000292648],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9465593,"threshold_uncertainty_score":0.9993495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0310848158395885,"score_gpt":0.2980595454444924,"score_spread":0.2669747296049039,"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."}}