{"id":"W2142980440","doi":"10.1109/wiiat.2008.200","title":"Empirical Analysis of the Rank Distribution of Relevant Documents in Web Search","year":2008,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Google","keywords":"Computer science; Information retrieval; Relevance (law); Rank (graph theory); Database transaction; Point (geometry); Transaction log; Empirical research; Search engine; World Wide Web; Data mining; Database; Mathematics; Statistics","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":[0.0003864537,0.00004992281,0.0002071533,0.0001760845,0.00003977154,0.000009605393,0.0006329128,0.00002667122,0.00002434203],"category_scores_gemma":[0.00006419243,0.00003066684,0.0001514121,0.00333126,0.00007071844,0.0001313986,0.0002390307,0.00006759189,0.000003680762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002439545,"about_ca_system_score_gemma":0.00007060292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003637944,"about_ca_topic_score_gemma":0.0001216371,"domain_scores_codex":[0.9989485,0.0001215294,0.0002693765,0.0001800945,0.0003606801,0.0001198314],"domain_scores_gemma":[0.9992132,0.00008449824,0.00006389956,0.0005498898,0.00006171596,0.00002677134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006361956,0.0001737436,0.9906,0.000005776408,0.0003003164,0.000004878288,0.0006521994,0.002169556,0.001069595,0.00136579,0.001682553,0.001969199],"study_design_scores_gemma":[0.0002195024,0.00002053173,0.6580782,0.000009589612,0.00009624002,0.00000140599,0.00004274104,0.3379886,0.003191982,0.00004183711,0.0002515315,0.0000579141],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9552472,0.00001774785,0.04364947,0.0006427118,0.00001580698,0.00002785101,0.00002162648,0.000009245913,0.0003683082],"genre_scores_gemma":[0.9986112,0.00002796609,0.001066308,0.00002681056,0.000003099969,9.740047e-7,0.00001894125,0.000001007029,0.000243667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.335819,"threshold_uncertainty_score":0.160056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03471606577078541,"score_gpt":0.308255431841216,"score_spread":0.2735393660704306,"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."}}