{"id":"W2763926089","doi":"10.48550/arxiv.1710.02058","title":"Skyline Computation with Noisy Comparisons","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Skyline; Computer science; Computation; Artificial intelligence; Data mining; 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":[0.002215935,0.00152602,0.002814123,0.002023957,0.001610084,0.003862206,0.004206702,0.002909806,0.008613719],"category_scores_gemma":[0.01780772,0.0009212962,0.001720759,0.004070874,0.00173705,0.008646103,0.005111898,0.002049132,0.003208703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001918598,"about_ca_system_score_gemma":0.002125392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003446438,"about_ca_topic_score_gemma":0.004795393,"domain_scores_codex":[0.9950641,0.001064527,0.000382567,0.001784439,0.001174719,0.0005296791],"domain_scores_gemma":[0.9892868,0.004302782,0.001054892,0.004052602,0.0009204129,0.0003824006],"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":[0.004652,0.0004715806,0.01364107,0.001229313,0.0005620951,0.0005926545,0.001249851,0.4436774,0.01503484,0.1177368,0.04696778,0.3541846],"study_design_scores_gemma":[0.0001737614,0.0001773744,0.001064381,0.00004841798,0.00005608823,0.0002550944,0.0002064883,0.8591134,0.007285465,0.1257595,0.005812588,0.00004739237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1073153,0.001148816,0.8679143,0.001376938,0.0001804806,0.0002860097,0.003628602,0.01148907,0.006660465],"genre_scores_gemma":[0.5356768,0.0002623105,0.449948,0.0004708301,0.0002092902,0.0004104437,0.006852561,0.0009923885,0.005177294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008613719,"threshold_uncertainty_score":0.02881569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1013317018962763,"score_gpt":0.2065412029415,"score_spread":0.1052095010452237,"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."}}