{"id":"W199178514","doi":"10.29173/cais134","title":"Exploring Web Co-link Patterns for Business Intelligence: The Case of Two Chinese Industries","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Web visibility and informetrics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Competition (biology); Business; Competitive intelligence; Business administration; Industrial organization; Humanities; Marketing; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00143115,0.0002739833,0.0002312587,0.005986717,0.001461523,0.001881447,0.0005547572,0.0006921982,0.001654444],"category_scores_gemma":[0.003724567,0.0002247933,0.0004170135,0.009595512,0.001062672,0.001316927,0.001355251,0.0004296772,0.0001792987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002002188,"about_ca_system_score_gemma":0.001361335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1017336,"about_ca_topic_score_gemma":0.1453414,"domain_scores_codex":[0.9993716,0.0002138409,0.00003796595,0.00007964629,0.0001652401,0.0001317621],"domain_scores_gemma":[0.9970962,0.001898552,0.000277279,0.0001995232,0.0003708898,0.0001576493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004397413,0.0005032717,0.6949573,0.0004402724,0.0001667213,0.01335998,0.09072482,0.01132069,0.01081366,0.01736423,0.001621456,0.1582879],"study_design_scores_gemma":[0.00005237678,0.0001504581,0.7484828,0.0001278296,0.0002411412,0.001766003,0.1034005,0.1145882,0.009368203,0.006498073,0.01523315,0.00009137749],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954765,0.00005731633,0.00106013,0.0001028362,0.000001312658,0.00001994385,0.00006590027,0.000009253926,0.003206753],"genre_scores_gemma":[0.9947936,0.00008706591,0.003864971,0.0000128107,0.000002589097,0.00002032558,0.0001383024,0.000007104652,0.001073077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9940133,"threshold_uncertainty_score":0.2022829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1131299979235427,"score_gpt":0.3033310254627592,"score_spread":0.1902010275392165,"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."}}