{"id":"W2806399785","doi":"","title":"Event Nugget Detection, Classification and Coreference Resolution using Deep Neural Networks and eXtreme Grandient Boosting.","year":2015,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Coreference; Boosting (machine learning); Computer science; Artificial intelligence; Event (particle physics); Artificial neural network; Resolution (logic); Deep neural networks; Pattern recognition (psychology); 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":[0.002647175,0.00079332,0.001344028,0.002085704,0.0008798258,0.001374274,0.002247239,0.001453712,0.002454634],"category_scores_gemma":[0.005758237,0.0004966361,0.0009459628,0.001744204,0.0004448953,0.002018775,0.002075539,0.002223107,0.001708539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007046201,"about_ca_system_score_gemma":0.0008247183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003382385,"about_ca_topic_score_gemma":0.007337334,"domain_scores_codex":[0.9987919,0.0003892991,0.00007069509,0.0003501107,0.0002297781,0.0001682807],"domain_scores_gemma":[0.9978635,0.001092206,0.0001738136,0.0003929215,0.000366034,0.0001115903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008229591,0.0003936244,0.004365352,0.0002002125,0.0002291725,0.0003194092,0.0002986477,0.07691407,0.01419628,0.01436303,0.0269562,0.860941],"study_design_scores_gemma":[0.00001935391,0.00004022276,0.001109277,0.00001702991,0.00004156401,0.00009398198,0.00005045026,0.9716813,0.005557558,0.01853293,0.002842905,0.00001346848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04455399,0.001817867,0.945703,0.000537295,0.0002360809,0.0001132182,0.0005168632,0.002469963,0.004051738],"genre_scores_gemma":[0.6022632,0.0006689662,0.3810285,0.0003933013,0.000447721,0.000176989,0.002928667,0.0002810048,0.0118116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003382385,"threshold_uncertainty_score":0.01399976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0550547200623276,"score_gpt":0.2660413638377407,"score_spread":0.2109866437754132,"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."}}