{"id":"W2401480511","doi":"","title":"NUS at TAC 2008: Augumenting Timestamped Graphs with Event Information and Selectively Expanding Opinion Contexts.","year":2008,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Event (particle physics); Computer science; Physics; Astrophysics","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":[0.002654582,0.0009302221,0.0009470838,0.002698348,0.0009521546,0.00196023,0.001701084,0.001364942,0.005094245],"category_scores_gemma":[0.01742178,0.0004631823,0.001011131,0.002243749,0.0005775223,0.0053102,0.002611758,0.002039842,0.003218853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009965138,"about_ca_system_score_gemma":0.001188479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01077094,"about_ca_topic_score_gemma":0.02768837,"domain_scores_codex":[0.998461,0.0007049273,0.00007541854,0.0003147622,0.0003292042,0.0001145914],"domain_scores_gemma":[0.9946886,0.002409409,0.0002500642,0.001525662,0.0008473975,0.0002789085],"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":[0.001428909,0.0004074438,0.009217609,0.0005885605,0.0002984598,0.0004588236,0.001634028,0.03544863,0.009656866,0.06258467,0.3607107,0.5175653],"study_design_scores_gemma":[0.000207498,0.0001466917,0.004039137,0.0001057049,0.0001385162,0.000266418,0.0006513241,0.7263168,0.0070965,0.1752752,0.085679,0.00007718008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09177887,0.004312418,0.8096427,0.004829449,0.002023108,0.0004556413,0.03461125,0.03590761,0.01643902],"genre_scores_gemma":[0.529018,0.000992202,0.3953656,0.0007876337,0.001037615,0.0003596406,0.05322894,0.002414052,0.01679638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01077094,"threshold_uncertainty_score":0.02141649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007914126589950565,"score_gpt":0.23338932594666,"score_spread":0.2254751993567094,"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."}}