{"id":"W2294150579","doi":"","title":"University of Amsterdam at TAC 2011: English slot filling task (Draft)","year":2011,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Relation (database); Task (project management); Matching (statistics); Tuple; Population; Track (disk drive); Information retrieval; World Wide Web; Artificial intelligence; Database; Mathematics; Statistics; 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":[0.005162245,0.001444589,0.001727542,0.001775935,0.002583607,0.004615897,0.002028829,0.002449185,0.1019876],"category_scores_gemma":[0.01685652,0.001349925,0.0008319467,0.003144342,0.0004458327,0.003976077,0.002270533,0.002755814,0.1187365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001393739,"about_ca_system_score_gemma":0.003967605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03060864,"about_ca_topic_score_gemma":0.03906704,"domain_scores_codex":[0.996135,0.001132489,0.0003871743,0.0009211972,0.0008958317,0.0005283698],"domain_scores_gemma":[0.9897259,0.001944109,0.0002302841,0.002099403,0.004564185,0.001435999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004004086,0.0002360306,0.0008178788,0.0003126279,0.00003125338,0.0001973337,0.0005492087,0.000826472,0.002524548,0.0009381851,0.9543703,0.03879571],"study_design_scores_gemma":[0.0004034793,0.0002422533,0.009825837,0.0002373426,0.00006336512,0.0004275686,0.001511398,0.01166999,0.01053882,0.004381437,0.9605086,0.0001898366],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.06436358,0.002247909,0.06112516,0.009203936,0.0052987,0.002642518,0.6063235,0.06630358,0.1824911],"genre_scores_gemma":[0.08298033,0.0004270173,0.06320888,0.0009582616,0.000463121,0.00236593,0.759078,0.008731717,0.08178684],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1019876,"threshold_uncertainty_score":0.3411826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01315657950568141,"score_gpt":0.197969476123265,"score_spread":0.1848128966175836,"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."}}