{"id":"W2737275827","doi":"","title":"SUMMA at TAC Knowledge Base Population Task 2017.","year":2017,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Task (project management); Base (topology); Knowledge base; Computer science; Population; Artificial intelligence; Mathematics; Medicine; Engineering; Environmental health; Systems engineering","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":[0.0313018,0.00190005,0.002517895,0.005494955,0.005394286,0.008282644,0.005276246,0.004892107,0.06469362],"category_scores_gemma":[0.09147249,0.0007332688,0.001523073,0.004343365,0.001305429,0.009032308,0.01045711,0.005010106,0.05314168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003629396,"about_ca_system_score_gemma":0.01787788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03542819,"about_ca_topic_score_gemma":0.06576256,"domain_scores_codex":[0.9865893,0.004609284,0.0008106136,0.001287351,0.005571258,0.001132203],"domain_scores_gemma":[0.8979248,0.0309712,0.002108386,0.01018207,0.04228274,0.01653079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001816147,0.0001742464,0.0004456477,0.000334257,0.00003851519,0.00005360182,0.0001688601,0.0004512013,0.0004882135,0.0008824337,0.960485,0.03629643],"study_design_scores_gemma":[0.0005049541,0.0002860333,0.004387984,0.0008623852,0.0001560644,0.0001261604,0.001676228,0.01137496,0.005293494,0.01956096,0.9556352,0.0001354855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.04581096,0.01127077,0.09795197,0.1384324,0.03643723,0.007420034,0.4892497,0.03210475,0.1413222],"genre_scores_gemma":[0.06742236,0.00263636,0.07043771,0.009023664,0.005690684,0.00500143,0.6978812,0.005592737,0.1363138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06469362,"threshold_uncertainty_score":0.2164217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09041987003507082,"score_gpt":0.4039581842127519,"score_spread":0.3135383141776811,"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."}}