{"id":"W2133623058","doi":"10.14778/1687627.1687729","title":"Creating competitive products","year":2009,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Skyline; Dominance (genetics); Set (abstract data type); Computer science; Competitive advantage; Data mining; Business; Marketing","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":[0.0002495003,0.0001042509,0.0001161543,0.00005256068,0.000126618,0.0001415038,0.001266232,0.00001366947,0.000004025796],"category_scores_gemma":[0.00006792843,0.00007003898,0.00004455069,0.0004022332,0.0000314223,0.0006108708,0.0004561357,0.00007286852,0.000009992174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002888567,"about_ca_system_score_gemma":0.00001122007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006572749,"about_ca_topic_score_gemma":1.56301e-7,"domain_scores_codex":[0.999026,0.000003409898,0.0001725942,0.0002720499,0.0003251069,0.0002008634],"domain_scores_gemma":[0.9994711,0.00001124123,0.0001613988,0.0001885259,0.0001372414,0.00003045192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003708058,0.000128904,0.0004104213,0.00003479072,0.00001927734,5.602468e-7,0.000662608,0.000002843001,0.01557531,0.9446012,0.004319823,0.0342405],"study_design_scores_gemma":[0.001422418,0.0006223522,0.03279612,0.0004653303,0.00006334319,0.00002200189,0.0008078724,0.006621058,0.8368195,0.06675237,0.05292233,0.0006852864],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0867401,0.0004020935,0.007099385,0.05181239,0.00137435,0.002536155,0.00001282321,0.0006803196,0.8493424],"genre_scores_gemma":[0.9607009,0.0000183107,0.03717291,0.0004861972,0.0001053931,0.00001115313,8.573751e-7,0.000004300976,0.001500024],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8778489,"threshold_uncertainty_score":0.2856107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01145182703798596,"score_gpt":0.2180680133827352,"score_spread":0.2066161863447492,"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."}}