{"id":"W2408078294","doi":"","title":"Using a weakly supervised approach and lexical patterns for the KBP slot filling task.","year":2011,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Task (project management); Computer science; Identification (biology); Relation (database); Artificial intelligence; Natural language processing; Population; Track (disk drive); Knowledge base; Component (thermodynamics); Data mining; Engineering; Biology","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":[0.000435696,0.00007404673,0.00009921905,0.00002830857,0.0002325465,0.00004062105,0.0003174695,0.00003231296,0.00000263257],"category_scores_gemma":[0.00001290131,0.00005264636,0.0000236499,0.00007814029,0.0001468598,0.0001426878,0.0001150215,0.000051193,2.394571e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003200565,"about_ca_system_score_gemma":0.00001822996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003261708,"about_ca_topic_score_gemma":0.000001125808,"domain_scores_codex":[0.9994642,0.00003545522,0.0001406386,0.000193734,0.00005728781,0.0001086895],"domain_scores_gemma":[0.9992965,0.0002368913,0.00004901645,0.0003411109,0.00004483713,0.00003161724],"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":[0.00001108764,0.00001936229,0.0001325177,0.00003639203,0.00001072629,3.01095e-8,0.002459371,0.00003924041,0.0005867431,0.9775835,0.000001451546,0.01911963],"study_design_scores_gemma":[0.0002705957,0.00003838498,0.0006437838,0.00001192587,0.00005114297,0.00001592951,0.002241835,0.2093086,0.006194982,0.7803922,0.0006445109,0.0001860697],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04485682,0.0004372436,0.9538399,0.00006610237,0.00001658888,0.0003039281,0.000006282706,0.00002908194,0.0004440541],"genre_scores_gemma":[0.9411984,0.00002573703,0.0585087,0.00004672904,0.00004319588,0.0001344991,0.000001845245,0.000005011944,0.00003585056],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8963416,"threshold_uncertainty_score":0.2146856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06256469848337742,"score_gpt":0.267818551467447,"score_spread":0.2052538529840696,"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."}}