{"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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002405224,0.0001368002,0.0001708945,0.0004718056,0.0001983752,0.0001897466,0.0006685067,0.00009814848,0.00006282537],"category_scores_gemma":[0.0007744184,0.0001213293,0.00005316428,0.001003668,0.00007935969,0.01490544,0.0001200646,0.0001223579,0.00005030539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001595895,"about_ca_system_score_gemma":0.0001912129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001924231,"about_ca_topic_score_gemma":0.00001287322,"domain_scores_codex":[0.9975449,0.0001642313,0.0007841858,0.0001291626,0.001123545,0.0002540014],"domain_scores_gemma":[0.9973635,0.00002768713,0.0005436534,0.0004335371,0.001533508,0.00009811391],"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":[0.00005108278,0.0001223624,0.05546548,0.0002817112,0.00003934571,8.110371e-7,0.06837668,0.000523102,0.000192687,0.07022832,0.00006991655,0.8046485],"study_design_scores_gemma":[0.001400569,0.0009044246,0.2520013,0.0002380132,0.00009058721,0.00003568204,0.003910412,0.6879528,0.0282731,0.02355297,0.000994457,0.0006455918],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8134788,0.0000536115,0.1740076,0.000005455556,0.0003070086,0.0004921099,0.00001079546,0.0001690214,0.01147564],"genre_scores_gemma":[0.9746085,0.00001335235,0.02521044,0.00003714565,0.00001717126,0.00004835445,0.00004224639,0.000004208294,0.00001862302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8040029,"threshold_uncertainty_score":0.9988726,"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."}}