{"id":"W2805756377","doi":"","title":"Bootstrapped Self Training for Knowledge Base Population.","year":2015,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Computer science; Base (topology); Knowledge base; Population; Artificial intelligence; Mathematics; Geography; Demography; Sociology","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":[0.002940369,0.0004713141,0.000898827,0.001357494,0.0007293622,0.0008176464,0.002543416,0.001469342,0.005539616],"category_scores_gemma":[0.01417179,0.0004106015,0.000521269,0.001004961,0.0007332852,0.001997528,0.00181717,0.001272667,0.001593096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006111236,"about_ca_system_score_gemma":0.001027295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002506261,"about_ca_topic_score_gemma":0.004007401,"domain_scores_codex":[0.9987691,0.0005025769,0.00006332694,0.0002665955,0.0002912656,0.0001071688],"domain_scores_gemma":[0.9937114,0.003464422,0.0001676946,0.001156871,0.001314473,0.0001851615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004365756,0.0005863245,0.004915712,0.000270462,0.0001185458,0.0001786224,0.0003745198,0.2137878,0.005365937,0.01886457,0.02138532,0.7337157],"study_design_scores_gemma":[0.00003773319,0.0001033471,0.0005079558,0.00003487719,0.00002453791,0.00007181852,0.00007448101,0.9821692,0.002686471,0.01172957,0.002552737,0.000007291391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08003341,0.0008921553,0.904378,0.0005446671,0.0002216595,0.0004755516,0.0006164939,0.003077798,0.009760204],"genre_scores_gemma":[0.6370212,0.0002506392,0.3512452,0.0005790192,0.0001394057,0.0007237195,0.002419319,0.0002897292,0.007331781],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005539616,"threshold_uncertainty_score":0.01853192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02952696293558689,"score_gpt":0.2960126789356213,"score_spread":0.2664857160000345,"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."}}