{"id":"W2117777550","doi":"10.1155/2013/915963","title":"A Relation Routing Scheme for Distributed Semantic Media Query","year":2013,"lang":"en","type":"article","venue":"The Scientific World JOURNAL","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hunan University of Science and Technology; Natural Science Foundation of Beijing Municipality; National Institute on Alcohol Abuse and Alcoholism; Max-Planck-Gesellschaft; Hunan University; National Natural Science Foundation of China; Sun Yat-sen University; Natural Science Foundation of Hunan Province; University of Ottawa","keywords":"Computer science; Scalability; Semantic computing; Routing (electronic design automation); Scheme (mathematics); Relation (database); Semantic query; Information retrieval; Distributed computing; Data mining; Computer network; Semantic Web; Database; Web search query; Search engine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002224529,0.0001040021,0.0001144713,0.0001871622,0.001375356,0.002202323,0.0009608794,0.00002318299,0.00003521261],"category_scores_gemma":[0.0002604271,0.00006793103,0.0001423691,0.0007144064,0.0001004744,0.0008433632,0.0001517551,0.0003138428,0.0001401522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000643989,"about_ca_system_score_gemma":0.00008909595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003044011,"about_ca_topic_score_gemma":0.00004127865,"domain_scores_codex":[0.9985328,0.0001046431,0.0003177903,0.0002526414,0.0004250634,0.0003670818],"domain_scores_gemma":[0.9986458,0.0003160924,0.0002086433,0.0004389597,0.0002827165,0.000107808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005014212,0.0003074899,0.008216967,0.00004713453,0.0002374342,0.00003566334,0.008796726,0.002436007,0.09729732,0.1349784,0.6063669,0.1412299],"study_design_scores_gemma":[0.0008144407,0.00002849231,0.01267178,0.0001824033,0.00003111309,0.0002145707,0.0003197753,0.9333381,0.0005997761,0.04252102,0.008945027,0.0003335051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3061541,0.0003134316,0.6708353,0.0142258,0.00757436,0.0003793763,0.000005892347,0.0001553395,0.0003563375],"genre_scores_gemma":[0.9916353,0.000002301418,0.003736723,0.00014266,0.0002999934,0.00001140316,0.000007661743,0.000006597932,0.004157334],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9309021,"threshold_uncertainty_score":0.9999247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02349512909464218,"score_gpt":0.2286894332662147,"score_spread":0.2051943041715725,"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."}}