{"id":"W2807542997","doi":"","title":"IECAS Event Detection System at TAC KBP 2017 Event Nugget Track.","year":2017,"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":"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":[0.003023613,0.001110469,0.001089521,0.004246809,0.001016441,0.002670522,0.001535129,0.001081701,0.01797951],"category_scores_gemma":[0.009377388,0.0004092419,0.0003360435,0.002120615,0.0002445425,0.002925368,0.001470337,0.00154633,0.01967313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093886,"about_ca_system_score_gemma":0.00199168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02109972,"about_ca_topic_score_gemma":0.02740892,"domain_scores_codex":[0.9978569,0.0003357015,0.0001584253,0.0005211998,0.000966887,0.0001608757],"domain_scores_gemma":[0.9947745,0.0009132733,0.0003139016,0.0007327808,0.002783304,0.0004822021],"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":[0.00132802,0.0003160386,0.01320819,0.0005100554,0.0001594182,0.0003483334,0.0005887642,0.003826733,0.009528226,0.002823214,0.8371094,0.1302536],"study_design_scores_gemma":[0.0006682696,0.0004957163,0.02564678,0.000241262,0.000240358,0.0003435204,0.001148355,0.2137423,0.03420703,0.01016046,0.7129046,0.0002012245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.07724719,0.001597874,0.1616233,0.002725982,0.002380171,0.001663931,0.2899669,0.3854659,0.0773287],"genre_scores_gemma":[0.2307241,0.0005112202,0.1169461,0.0006897387,0.0005793804,0.0009754045,0.6013674,0.007606035,0.04060061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02109972,"threshold_uncertainty_score":0.0601474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01379581950313419,"score_gpt":0.2651837489443339,"score_spread":0.2513879294411998,"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."}}