{"id":"W2391604923","doi":"","title":"An Advanced the Forecasting Strategy for Intelligence Topic Relativity Based on PageRank","year":2010,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; PageRank; Competitive intelligence; Web page; Quality (philosophy); Information retrieval; Computational intelligence; World Wide Web; Data science; Artificial intelligence; Knowledge management","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":[0.0021123,0.001186492,0.001372763,0.004532148,0.001240376,0.002884506,0.001577319,0.001159379,0.002376083],"category_scores_gemma":[0.009024449,0.0003975946,0.0008566533,0.003283653,0.0009160087,0.005533983,0.0009558662,0.001507926,0.001035781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00195311,"about_ca_system_score_gemma":0.002051865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008411792,"about_ca_topic_score_gemma":0.005311311,"domain_scores_codex":[0.9975521,0.0005227959,0.0001651031,0.000541347,0.0009983395,0.0002203491],"domain_scores_gemma":[0.996733,0.0009795473,0.0003343679,0.0002531738,0.001531516,0.0001685501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001917671,0.0001887053,0.01150627,0.000379077,0.0002286342,0.0003151417,0.0005561353,0.2910626,0.006788457,0.1652278,0.02176896,0.5017865],"study_design_scores_gemma":[0.00002704464,0.00005649903,0.001258325,0.00001729964,0.00004353595,0.0001176778,0.00006474724,0.9506426,0.00194236,0.04098593,0.004795335,0.00004864973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02717791,0.001242297,0.9619373,0.0007957934,0.0002915745,0.0001679161,0.0003091782,0.001089155,0.006988814],"genre_scores_gemma":[0.7163303,0.002215195,0.2672834,0.0002386335,0.000929419,0.0003833828,0.001204672,0.0002238343,0.01119113],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008411792,"threshold_uncertainty_score":0.01672566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03311330771514345,"score_gpt":0.2947385013842957,"score_spread":0.2616251936691523,"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."}}