{"id":"W2805736953","doi":"","title":"REDES at TAC Knowledge Base Population 2016 : EDL and BeSt tracks.","year":2016,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Base (topology); Computer science; Knowledge base; Population; Artificial intelligence; Mathematics; Demography; Mathematical analysis","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":[0.008540756,0.000817292,0.0009215069,0.006207281,0.001703157,0.006113783,0.002934479,0.001673324,0.02569362],"category_scores_gemma":[0.04549226,0.0009343388,0.001033912,0.006120152,0.0006008009,0.01326908,0.004263995,0.002601076,0.01619013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00230594,"about_ca_system_score_gemma":0.005464763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01885472,"about_ca_topic_score_gemma":0.03632708,"domain_scores_codex":[0.9955552,0.001234979,0.0003801985,0.0009823546,0.001517504,0.0003296274],"domain_scores_gemma":[0.9788162,0.005795658,0.0005963714,0.007992377,0.005286993,0.001512525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005613433,0.0003891833,0.008560446,0.0004730206,0.0001213147,0.0001046553,0.0007163316,0.008541968,0.001477394,0.01820164,0.4376863,0.5231664],"study_design_scores_gemma":[0.0002880712,0.000287207,0.006769297,0.0004797672,0.0001859012,0.0003776847,0.001110525,0.1489711,0.009354836,0.06504229,0.7669983,0.0001351186],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07591596,0.005932938,0.4441255,0.01126415,0.003064578,0.001154548,0.2208009,0.1335303,0.1042111],"genre_scores_gemma":[0.1980956,0.001731244,0.3815264,0.001235714,0.0005015702,0.0007498662,0.3383747,0.01126079,0.06652418],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02569362,"threshold_uncertainty_score":0.08595371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360623403106527,"score_gpt":0.2543820827541767,"score_spread":0.2407758487231114,"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."}}