{"id":"W2295082727","doi":"","title":"Stanford's 2013 KBP System","year":2013,"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":"Consistency (knowledge bases); Inference; Computer science; Component (thermodynamics); Data mining; Information retrieval; Artificial intelligence","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":[0.003712098,0.001987052,0.001938996,0.00537463,0.002538008,0.00336741,0.004192054,0.001926548,0.08539944],"category_scores_gemma":[0.01461354,0.001524823,0.001045905,0.004801452,0.0006247048,0.007683036,0.005155904,0.003400763,0.08802921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001889462,"about_ca_system_score_gemma":0.004181813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0364063,"about_ca_topic_score_gemma":0.03103588,"domain_scores_codex":[0.9966666,0.0005543008,0.0005300097,0.0007896568,0.001247204,0.0002122536],"domain_scores_gemma":[0.9929004,0.001691276,0.0002358161,0.001791405,0.002916628,0.0004646492],"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":[0.000305337,0.0001786234,0.0007426947,0.0007420351,0.00004840011,0.0002364399,0.0003545924,0.0009315504,0.003348444,0.003686235,0.8853605,0.1040651],"study_design_scores_gemma":[0.0003851862,0.0001504602,0.004630377,0.0003004064,0.0001297589,0.0006966797,0.0006101882,0.02628846,0.01164523,0.01055717,0.9443393,0.0002668514],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01684314,0.001768685,0.1221257,0.002951812,0.001594736,0.001531115,0.3629063,0.4174474,0.07283112],"genre_scores_gemma":[0.05897292,0.0007840482,0.2010901,0.00115507,0.0003365276,0.001878688,0.6920559,0.01573399,0.02799286],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.08539944,"threshold_uncertainty_score":0.2856896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007980749315077551,"score_gpt":0.2188285240948304,"score_spread":0.2108477747797529,"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."}}