{"id":"W2915114476","doi":"","title":"RPI BLENDER TAC-KBP2016 System Description.","year":2016,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":14,"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004776946,0.00008185844,0.0001061762,0.00006884804,0.0001170704,0.00004678881,0.0004585741,0.00004565758,0.000006641988],"category_scores_gemma":[0.00002390342,0.00004993638,0.00002154095,0.0001739304,0.0001973238,0.0004426194,0.0001240129,0.00003843402,0.00001197973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001789661,"about_ca_system_score_gemma":0.00002980994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004364008,"about_ca_topic_score_gemma":4.329859e-7,"domain_scores_codex":[0.9993857,0.0000694787,0.0001524963,0.0001907096,0.00009402567,0.0001076204],"domain_scores_gemma":[0.9991678,0.0001683378,0.00009481271,0.0004247153,0.0001075957,0.00003672973],"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":[0.000005387988,0.000008770339,0.00001010079,0.00003794868,0.000005160623,2.100968e-7,0.000319845,3.292156e-8,0.01073306,0.9323204,0.00009110555,0.05646798],"study_design_scores_gemma":[0.00007936367,0.00001435116,0.00001459667,0.00003668092,0.000007278287,0.00001581176,0.0003225949,0.000007785527,0.1047692,0.8921407,0.002501172,0.00009044496],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001447526,0.002454375,0.9939263,0.0003334108,0.00002551281,0.0001461722,0.000004952712,0.0003817641,0.001280016],"genre_scores_gemma":[0.9528798,0.00004053431,0.04601797,0.0000280486,0.00003795889,0.0001197326,9.170292e-7,0.000005351414,0.0008696649],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9514323,"threshold_uncertainty_score":0.2036346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0084808463073163,"score_gpt":0.2374701232353894,"score_spread":0.2289892769280731,"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."}}