{"id":"W2408669150","doi":"","title":"Predicting user preferences - An evaluation of popular relevance metrics.","year":2011,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Relevance (law); Computer science; Information retrieval; Data science; Political science","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":[0.008759367,0.0007801563,0.001005049,0.00531498,0.0004583155,0.00130415,0.0008214446,0.001093314,0.001217505],"category_scores_gemma":[0.04977439,0.0002026831,0.0007108479,0.003935948,0.0002732422,0.002235243,0.0007199332,0.0008535173,0.0007751055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005040759,"about_ca_system_score_gemma":0.0005412285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002212042,"about_ca_topic_score_gemma":0.003802117,"domain_scores_codex":[0.9916236,0.004758673,0.0005110239,0.0004764815,0.002432778,0.0001974585],"domain_scores_gemma":[0.9575524,0.03565905,0.001184444,0.001863367,0.003088786,0.0006520458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003609139,0.001797224,0.1325998,0.001440755,0.001020793,0.00008669759,0.000425108,0.02001851,0.003669058,0.003560329,0.01867431,0.8130983],"study_design_scores_gemma":[0.0007596894,0.006723768,0.2000328,0.0004909706,0.001032124,0.001036053,0.0009034682,0.755364,0.007512273,0.01313107,0.01279201,0.0002218307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8605232,0.03175827,0.08778616,0.001059823,0.000285895,0.0007199459,0.004851058,0.00178162,0.01123407],"genre_scores_gemma":[0.9409567,0.002037243,0.05196426,0.00009825542,0.0001409762,0.0001841113,0.003350313,0.0000829905,0.001185169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008759367,"threshold_uncertainty_score":0.04632449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08037566889327485,"score_gpt":0.2885429737758956,"score_spread":0.2081673048826208,"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."}}