{"id":"W1998792254","doi":"10.1145/1247480.1247613","title":"URank","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Semantics (computer science); Ranking (information retrieval); Probabilistic logic; Information retrieval; Query language; Query optimization; Theoretical computer science; Artificial intelligence; Programming language","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":[0.0002042207,0.00002388866,0.00002022682,0.00003279678,0.00002141347,0.00006717185,0.0004196129,0.000005869426,0.00004490053],"category_scores_gemma":[0.000002790277,0.00001870736,0.000009931849,0.0001342164,0.000004814527,0.0003786281,0.0001459159,0.0000155034,0.0003622739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002856022,"about_ca_system_score_gemma":0.000001734959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006229077,"about_ca_topic_score_gemma":0.000003827398,"domain_scores_codex":[0.9996862,0.000001685849,0.00004414483,0.00008873456,0.00007621422,0.0001029732],"domain_scores_gemma":[0.9997407,0.00001101345,0.000006798894,0.0002102483,0.000006520611,0.00002471429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[1.79498e-7,0.000008063958,0.0001356553,6.350787e-7,0.000001759899,0.00001163456,0.00001643445,2.442935e-7,0.00003097325,0.5773432,0.01345936,0.4089919],"study_design_scores_gemma":[0.000285611,0.00003548085,0.01971317,0.00000249338,0.000001823463,0.000004870173,0.00002928053,0.02132647,0.003642272,0.01246238,0.9422868,0.0002093416],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002598264,0.000006182037,0.7689819,0.0003715857,0.0001362708,0.00001602359,6.090982e-8,0.0001103133,0.2301178],"genre_scores_gemma":[0.3342091,0.000005557625,0.6289988,0.002548922,0.0001438946,9.565319e-7,0.000002848794,0.000003587473,0.03408639],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9288275,"threshold_uncertainty_score":0.4656419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009667932734316846,"score_gpt":0.2364262225732772,"score_spread":0.2267582898389604,"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."}}