{"id":"W2805727849","doi":"","title":"UI CCG TAC-KBP2017 Submissions: Entity Discovery and Linking, and Event Nugget Detection and Co-reference.","year":2017,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Event (particle physics); Computer science; 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":[0.01312859,0.003565755,0.00303747,0.006278628,0.003922259,0.008118222,0.005334401,0.005136007,0.2141443],"category_scores_gemma":[0.06114899,0.001330785,0.00216828,0.00544526,0.000992148,0.006000506,0.008833889,0.003420711,0.1718897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002701175,"about_ca_system_score_gemma":0.007292287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02097822,"about_ca_topic_score_gemma":0.04848247,"domain_scores_codex":[0.9876923,0.003762725,0.0009102752,0.001423697,0.004906284,0.001304655],"domain_scores_gemma":[0.9409206,0.01348983,0.00142706,0.01214107,0.02243195,0.009589451],"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":[0.0001985659,0.00005120553,0.0001614007,0.0001815543,0.00001692733,0.00007874217,0.00003687458,0.0002319111,0.0004101642,0.0005204803,0.9902174,0.007894821],"study_design_scores_gemma":[0.0003939048,0.0001332711,0.002531989,0.0002188283,0.00004392049,0.0003693377,0.0002943359,0.009050394,0.003630699,0.006655429,0.9765725,0.0001055385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01092988,0.00256411,0.07054429,0.01329946,0.03963488,0.002963577,0.671537,0.1035019,0.08502488],"genre_scores_gemma":[0.01318652,0.0005027541,0.05054872,0.001173062,0.004024176,0.001380762,0.8346968,0.01834765,0.07613961],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.2141443,"threshold_uncertainty_score":0.7163839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01666441711421923,"score_gpt":0.2829101230503985,"score_spread":0.2662457059361792,"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."}}