{"id":"W2805435982","doi":"","title":"The ZHI-EDL System for Entity Discovery and Linking at TAC KBP 2017.","year":2017,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","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":[0.004529836,0.001508908,0.001227723,0.006592672,0.001182578,0.003871584,0.002767475,0.00135302,0.04378251],"category_scores_gemma":[0.01303472,0.001117103,0.001128988,0.004194766,0.0005154018,0.007016392,0.005899436,0.002056099,0.03912812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001131625,"about_ca_system_score_gemma":0.002660227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009102065,"about_ca_topic_score_gemma":0.01115893,"domain_scores_codex":[0.9978503,0.0006033304,0.0002952748,0.000484056,0.0006218156,0.0001452952],"domain_scores_gemma":[0.995926,0.001409291,0.0002511137,0.00143747,0.0007363522,0.0002398228],"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":[0.001018543,0.0002240966,0.003679557,0.00222375,0.0003705416,0.0005701976,0.001204427,0.005280965,0.007691645,0.02253974,0.6984357,0.2567608],"study_design_scores_gemma":[0.0005186942,0.0001508418,0.003919413,0.0003839807,0.0002189146,0.000406073,0.0006824521,0.102609,0.02168407,0.0416393,0.8275943,0.0001930964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.006298369,0.0008702967,0.3117216,0.0009140763,0.0003832298,0.00061465,0.1924551,0.4687828,0.01795989],"genre_scores_gemma":[0.04016807,0.0006578628,0.3523103,0.0003849685,0.0001527649,0.0009808232,0.5716699,0.01661499,0.01706032],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04378251,"threshold_uncertainty_score":0.1464671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01552013330431991,"score_gpt":0.2613283092236743,"score_spread":0.2458081759193544,"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."}}