{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006876733,0.00006185107,0.00009198813,0.00001430104,0.001495562,0.0003522828,0.0005645307,0.00002844873,1.892327e-7],"category_scores_gemma":[0.00003371388,0.00004372583,0.00002286532,0.00002040176,0.000257886,0.0003920977,0.0003486723,0.00003574866,9.358281e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009770007,"about_ca_system_score_gemma":0.00001800397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001341512,"about_ca_topic_score_gemma":0.00001241906,"domain_scores_codex":[0.9995061,0.00002842903,0.0001280505,0.0001749385,0.00006321889,0.00009922154],"domain_scores_gemma":[0.9987023,0.0003224759,0.0001507394,0.0007561105,0.00004352529,0.00002478201],"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":[0.000008440256,0.000003688411,0.0002221725,0.00005768666,0.000007644583,6.147572e-8,0.0002361974,0.000004558862,0.0002555158,0.9799772,0.00001145164,0.01921542],"study_design_scores_gemma":[0.0002604379,0.00002709561,0.00141312,0.00003801892,0.00002942385,0.00001366051,0.0005715999,0.00370003,0.008203645,0.9730198,0.01256764,0.0001555619],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05681264,0.00106833,0.9397666,0.0003791313,0.00009054573,0.0002979846,0.000008154075,0.00003131865,0.001545308],"genre_scores_gemma":[0.9974183,0.00009917387,0.001467941,0.00001020013,0.00007693552,0.0001404867,0.000001666038,0.000003231866,0.0007819947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9406057,"threshold_uncertainty_score":0.9998044,"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."}}