{"id":"W2806219291","doi":"","title":"WIP Event Detection System in 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":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Track (disk drive); Event (particle physics); Computer science; Real-time computing; Operating system; Physics","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":[0.001773111,0.001039941,0.001114642,0.003805619,0.0009881228,0.001801623,0.001870623,0.001015214,0.01215667],"category_scores_gemma":[0.007730387,0.0004975487,0.0003949951,0.002227596,0.000216136,0.00372174,0.001584408,0.001230876,0.01248594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007536641,"about_ca_system_score_gemma":0.001596782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01485238,"about_ca_topic_score_gemma":0.01519716,"domain_scores_codex":[0.9985999,0.0001638987,0.0001484104,0.0004228122,0.0005533734,0.0001114448],"domain_scores_gemma":[0.9971071,0.0006596788,0.0002155134,0.000503986,0.001291591,0.0002221379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001692139,0.0002851701,0.01179032,0.001373542,0.000208176,0.0005966136,0.0007085931,0.005698103,0.01564658,0.003315837,0.6680231,0.2906618],"study_design_scores_gemma":[0.000520067,0.0005901224,0.02998163,0.0002966207,0.0003612947,0.000711302,0.001306888,0.3485648,0.06410485,0.01411572,0.539189,0.0002577043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.07707967,0.002396525,0.2788764,0.001619554,0.001191883,0.001525516,0.2294412,0.3713687,0.03650049],"genre_scores_gemma":[0.2872953,0.0007674349,0.1914894,0.0006383762,0.0002648544,0.00134163,0.4856939,0.005788067,0.02672108],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01485238,"threshold_uncertainty_score":0.04066807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0134719794459099,"score_gpt":0.2596017377283051,"score_spread":0.2461297582823952,"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."}}