{"id":"W2806889342","doi":"","title":"The YorkNRM Systems for Trilingual EDL Tasks at TAC KBP 2016.","year":2016,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Natural language processing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008498638,0.00008696732,0.0001116085,0.00003386874,0.0003919207,0.00007698357,0.0006358249,0.00004949456,0.000001359486],"category_scores_gemma":[0.0001091947,0.00004417107,0.00003112772,0.0001243779,0.0002997599,0.0001676207,0.0001618039,0.00003657682,0.000003632617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001726841,"about_ca_system_score_gemma":0.00004419364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005959411,"about_ca_topic_score_gemma":0.000001646212,"domain_scores_codex":[0.9993364,0.00005569544,0.0001850138,0.0001903594,0.00009055316,0.0001419721],"domain_scores_gemma":[0.9980938,0.001108265,0.0001410118,0.0004830055,0.0001409454,0.00003297287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002779407,0.000006878759,0.000004805012,0.00002208442,0.000007095709,5.459365e-8,0.0001653556,1.81645e-7,0.003222703,0.9161465,0.0006180865,0.07977843],"study_design_scores_gemma":[0.0001311424,0.00004318693,0.000004187577,0.00002214224,0.000009462771,0.000007791934,0.0001119543,0.00003755649,0.0691263,0.8662308,0.0641816,0.00009386439],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001247143,0.01697879,0.9798188,0.0007057089,0.0000718876,0.0004924278,0.00001982951,0.0001870883,0.0004783141],"genre_scores_gemma":[0.9840025,0.0004308197,0.009659628,0.00003785099,0.0001363367,0.0006819361,0.000003400565,0.000009643718,0.005037848],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9827554,"threshold_uncertainty_score":0.3014377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008514998930767157,"score_gpt":0.2669674632155833,"score_spread":0.2584524642848162,"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."}}