{"id":"W2806238373","doi":"","title":"Overview of TAC KBP 2015 Event Nugget Track.","year":2015,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Track (disk drive); Computer science; Event (particle physics); Physics; Operating system","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":[0.0108763,0.002292875,0.002604146,0.01176513,0.003218965,0.009216939,0.00603569,0.002391862,0.06060578],"category_scores_gemma":[0.02558411,0.001649137,0.001329804,0.009747802,0.0007339686,0.0148748,0.005719463,0.003680313,0.05569966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003850638,"about_ca_system_score_gemma":0.007718625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04852623,"about_ca_topic_score_gemma":0.04918781,"domain_scores_codex":[0.9942154,0.001099635,0.0004473634,0.0009412256,0.0029434,0.0003529153],"domain_scores_gemma":[0.9874653,0.002899604,0.0004988037,0.001989277,0.005839779,0.001307451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000369142,0.0001946335,0.001080453,0.0009328913,0.00009722197,0.0001289294,0.0003289269,0.001940156,0.002254477,0.007761361,0.8723721,0.1125398],"study_design_scores_gemma":[0.0001678347,0.0001659278,0.002240204,0.0003550429,0.0001071809,0.0002327382,0.0002928493,0.02046898,0.003560735,0.01184106,0.9604649,0.000102542],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01304576,0.01524105,0.2722058,0.01102228,0.004709783,0.004196831,0.3464201,0.1782219,0.1549364],"genre_scores_gemma":[0.02880719,0.004579799,0.1409885,0.001713297,0.000831396,0.002501465,0.7524266,0.01332277,0.05482901],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.06060578,"threshold_uncertainty_score":0.2027465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03524716365777896,"score_gpt":0.306960157542483,"score_spread":0.271712993884704,"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."}}