{"id":"W2185312150","doi":"","title":"SemLinker system for KBP2013: A disambiguation algorithm based on mutual relations of semantic annotations inside a document.","year":2013,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Entity linking; Annotation; Information retrieval; Process (computing); Ranking (information retrieval); Natural language processing; Artificial intelligence; Programming language; 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":[0.0003931833,0.0001094786,0.00018943,0.0001474917,0.0001918674,0.00004270064,0.0002620933,0.00005698843,0.000008006858],"category_scores_gemma":[0.000082874,0.00009360268,0.00005356688,0.0002992043,0.0001964347,0.0003393071,0.00004191686,0.00004843403,0.00001413431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001593015,"about_ca_system_score_gemma":0.00006240571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006507893,"about_ca_topic_score_gemma":0.000005242941,"domain_scores_codex":[0.9990947,0.00008387564,0.0003444716,0.0002159094,0.0001366632,0.0001244089],"domain_scores_gemma":[0.9980374,0.001006957,0.0002153084,0.0004430269,0.0002594689,0.00003782092],"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":[0.000009805634,0.00005804042,0.0001667264,0.00008461079,0.00001799407,5.604432e-8,0.0006467862,0.0002323087,0.0004405588,0.9722239,0.00008960152,0.02602958],"study_design_scores_gemma":[0.0008360148,0.00024695,0.008193354,0.00008603842,0.00009487002,0.000005220333,0.00344002,0.1021453,0.01667743,0.8673396,0.0006609882,0.0002741583],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01976769,0.0001106313,0.9775935,0.0005072557,0.00004591405,0.0008769622,0.0000187216,0.00009085743,0.0009884252],"genre_scores_gemma":[0.9584311,0.000005768654,0.04044142,0.00004199326,0.00002614094,0.0008558853,0.0000276967,0.000006552952,0.0001635023],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9386634,"threshold_uncertainty_score":0.3817007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00913259396379512,"score_gpt":0.2455256997393294,"score_spread":0.2363931057755343,"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."}}