{"id":"W2188437695","doi":"","title":"LCC Approaches to Knowledge Base Population at TAC 2010.","year":2010,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Surprise; Knowledge base; Computer science; Task (project management); Context (archaeology); Population; Base (topology); Relation (database); Track (disk drive); Artificial intelligence; Data mining; Engineering; Mathematics; Geography; Systems engineering","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":[0.0004934923,0.0000732539,0.00009231557,0.00006467528,0.0001548242,0.0000320741,0.0003286912,0.00004369474,0.00001442307],"category_scores_gemma":[0.00002890113,0.00006653261,0.0000192454,0.0001753549,0.00006911733,0.0001689565,0.0001991944,0.0000706545,0.0000251932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007606932,"about_ca_system_score_gemma":0.00001716858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001741358,"about_ca_topic_score_gemma":0.00003475853,"domain_scores_codex":[0.9994297,0.00003645111,0.0001445831,0.000218929,0.0000633155,0.0001070008],"domain_scores_gemma":[0.9991782,0.0001240375,0.00005099726,0.0005395394,0.00003711183,0.00007006559],"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":[0.000004617507,0.00002237165,0.0003436521,0.00001308304,0.000002602973,2.894618e-8,0.000643529,0.00003557175,0.001893862,0.957226,0.00003640432,0.0397783],"study_design_scores_gemma":[0.0001134272,0.00001839293,0.003349308,0.00000395352,0.00001018575,0.000006127138,0.0001320131,0.003960737,0.017054,0.966989,0.008194643,0.00016814],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1782027,0.000125717,0.8165957,0.0003907974,0.00008668857,0.0002443487,0.000003236875,0.00006826095,0.00428251],"genre_scores_gemma":[0.9788351,0.000003084241,0.01974443,0.00002955796,0.00007770625,0.0001254883,0.000007311464,0.000004689985,0.001172626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8006324,"threshold_uncertainty_score":0.2713121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04039580635658899,"score_gpt":0.25342152675725,"score_spread":0.213025720400661,"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."}}