{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00102822,0.000115217,0.0001758258,0.00006224896,0.0003134898,0.00009089984,0.000263922,0.0000678746,0.000002384786],"category_scores_gemma":[0.00002006677,0.0001047746,0.00002980073,0.000119378,0.0002064187,0.0004513447,0.0003784406,0.00009267133,0.000004865174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002290641,"about_ca_system_score_gemma":0.00002497346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001678089,"about_ca_topic_score_gemma":0.0000011439,"domain_scores_codex":[0.9990909,0.0000719944,0.0002560709,0.0002487012,0.0001218736,0.0002104375],"domain_scores_gemma":[0.9991482,0.0001099422,0.000135884,0.0004445463,0.00007051309,0.00009086099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007006599,0.00002906995,0.001289171,0.0001421525,0.00001208292,1.128398e-7,0.003933455,0.00003961849,0.0005126807,0.9821385,0.000002572225,0.01189359],"study_design_scores_gemma":[0.002240606,0.0001550306,0.01593617,0.0002259922,0.0002663331,0.0006005905,0.009321088,0.03456259,0.1291449,0.7903655,0.01505534,0.002125868],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.394587,0.002244304,0.6015291,0.00001496206,0.00005727427,0.0001694672,0.00000355141,0.00008210415,0.001312195],"genre_scores_gemma":[0.9883037,0.0000281285,0.01112881,0.00001620329,0.0001897427,0.00007408773,0.000004691945,0.000007185833,0.0002474359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5937167,"threshold_uncertainty_score":0.4272584,"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."}}