{"id":"W2170896764","doi":"10.1109/icde.2009.102","title":"Ranking with Uncertain Scores","year":2009,"lang":"en","type":"article","venue":"Proceedings - International Conference on Data Engineering","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ranking (information retrieval); Computer science; Rank (graph theory); Data mining; Set (abstract data type); Uncertain data; Probabilistic logic; Learning to rank; Semantics (computer science); Information retrieval; Ranking SVM; Sampling (signal processing); Machine learning; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000203226,0.0001638946,0.0001084189,0.000204727,0.00004960925,0.0008419645,0.003157002,0.00002416885,0.00002798452],"category_scores_gemma":[0.00006593875,0.0001413128,0.00001425951,0.0002358431,0.00001205738,0.002664714,0.0004543117,0.0001533823,0.0000267147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003528153,"about_ca_system_score_gemma":0.00002086217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000615178,"about_ca_topic_score_gemma":6.575959e-7,"domain_scores_codex":[0.9986663,0.000001505633,0.0001506278,0.0004987636,0.0004578409,0.0002249264],"domain_scores_gemma":[0.9993753,0.00001480722,0.00006634299,0.0003546912,0.0001288861,0.00005997881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001416134,0.00004062847,0.000177861,0.00001269598,0.00004020184,0.00001675956,0.00009544526,0.0003385227,0.0009174052,0.9563231,0.001559122,0.04046408],"study_design_scores_gemma":[0.0003420239,0.0001117978,0.001146712,0.0001975963,0.000005966166,0.00001404872,0.00002699741,0.9878616,0.000475989,0.001624706,0.007923328,0.0002691812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008208024,0.00003667396,0.9368629,0.008066685,0.0007172441,0.0003218945,0.000075157,0.0009013112,0.04481014],"genre_scores_gemma":[0.9219407,0.0000373894,0.07716163,0.000325385,0.000181561,0.000008337062,0.0001506308,0.000009374357,0.000185035],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9875231,"threshold_uncertainty_score":0.8119083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05920357991017572,"score_gpt":0.2793436375045019,"score_spread":0.2201400575943261,"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."}}