{"id":"W2535211222","doi":"10.1145/2983323.2983894","title":"Learning to Rank System Configurations","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Rank (graph theory); Learning to rank; Set (abstract data type); Task (project management); Information retrieval; Query expansion; State (computer science); Data mining; Ranking (information retrieval); Artificial intelligence; Machine learning; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006124697,0.002728276,0.002188133,0.002658546,0.001155376,0.00302771,0.002225319,0.001928329,0.00406938],"category_scores_gemma":[0.04464189,0.0009545948,0.0009293297,0.001731277,0.001216401,0.00496854,0.002028301,0.002968519,0.003073138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001553013,"about_ca_system_score_gemma":0.001838874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002791682,"about_ca_topic_score_gemma":0.004276216,"domain_scores_codex":[0.9928856,0.003040734,0.0004641122,0.001877576,0.001106815,0.0006251009],"domain_scores_gemma":[0.9765483,0.01422994,0.001512929,0.004540284,0.002548884,0.0006197803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007324886,0.0004368226,0.01531647,0.0004274853,0.0002854153,0.0001916887,0.0002645481,0.5954027,0.007816905,0.004445021,0.01002559,0.3646549],"study_design_scores_gemma":[0.00004352775,0.0002624664,0.001095115,0.00002296755,0.00005459775,0.000135164,0.00008919459,0.9847563,0.005453841,0.007239822,0.0008096475,0.00003736066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2630039,0.001461338,0.7132357,0.0009031904,0.0001653064,0.0005949201,0.001246594,0.01253981,0.006849145],"genre_scores_gemma":[0.8785186,0.0002682594,0.1166168,0.000198538,0.0001106049,0.0002858581,0.002091516,0.0004244081,0.001485488],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006124697,"threshold_uncertainty_score":0.03239083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0200259087190832,"score_gpt":0.298411265939545,"score_spread":0.2783853572204618,"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."}}