{"id":"W2394859052","doi":"","title":"HITS' Monolingual and Cross-lingual Entity Linking System at TAC 2012: A Joint Approach.","year":2012,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Cluster analysis; Natural language processing; Joint (building); Entity linking; Knowledge base","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":[0.004108983,0.001825117,0.001416772,0.003871772,0.00207031,0.0031468,0.003119617,0.002747119,0.009483169],"category_scores_gemma":[0.007721946,0.001115518,0.001553697,0.003175539,0.0006062043,0.009069387,0.005778849,0.002098916,0.01480093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001154024,"about_ca_system_score_gemma":0.003655042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01525146,"about_ca_topic_score_gemma":0.02399156,"domain_scores_codex":[0.9961329,0.0008968799,0.0003861634,0.001102532,0.001068229,0.000413354],"domain_scores_gemma":[0.993338,0.001013705,0.0002999795,0.002203685,0.002502907,0.0006417402],"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":[0.00114081,0.0009771397,0.01021149,0.001025441,0.001031306,0.001856111,0.001748321,0.01210959,0.04404543,0.006150917,0.422219,0.4974844],"study_design_scores_gemma":[0.0003902768,0.001115738,0.01932783,0.0002028254,0.001088699,0.003261106,0.003060621,0.4311425,0.140616,0.01781726,0.3812096,0.0007675839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1115371,0.002194853,0.4655939,0.002078594,0.001289158,0.001215128,0.02534245,0.3506535,0.0400953],"genre_scores_gemma":[0.3171992,0.0005426901,0.4958932,0.001049838,0.0003633667,0.0007942648,0.1312958,0.00877202,0.04408969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01525146,"threshold_uncertainty_score":0.03172433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0180952552988818,"score_gpt":0.2577802106315116,"score_spread":0.2396849553326298,"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."}}