{"id":"W2077780773","doi":"10.14778/1920841.1920948","title":"Computing closed skycubes","year":2010,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Skyline; Linear subspace; Computer science; Representation (politics); Subspace topology; Computation; Theoretical computer science; Formal concept analysis; Closure (psychology); Space (punctuation); Algorithm; Data mining; Mathematics; Artificial intelligence","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":[0.001759141,0.0006639026,0.001219891,0.00162185,0.001195743,0.002606171,0.001559206,0.0007579528,0.005189117],"category_scores_gemma":[0.009843668,0.0005085262,0.00126971,0.002261128,0.001584271,0.00709819,0.004009876,0.00118148,0.0009046454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008973855,"about_ca_system_score_gemma":0.001123996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001800986,"about_ca_topic_score_gemma":0.002457627,"domain_scores_codex":[0.9975935,0.0006650238,0.0002038221,0.0004144141,0.0008190798,0.0003041546],"domain_scores_gemma":[0.9953087,0.002439487,0.0003799098,0.0009243291,0.0007603918,0.0001870876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000526197,0.0001524322,0.003971327,0.0007978328,0.0001571955,0.0003951885,0.00102779,0.2399948,0.01435628,0.5029123,0.009145083,0.2265635],"study_design_scores_gemma":[0.0000599346,0.0001265187,0.0004267893,0.00008736164,0.00002725192,0.0001910625,0.000512925,0.4583998,0.01093587,0.5151916,0.01400548,0.00003537635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0576981,0.000405744,0.9366391,0.0002673534,0.00005289114,0.0001235571,0.0006141682,0.0009479034,0.003251156],"genre_scores_gemma":[0.3531286,0.0005391901,0.6394295,0.0001568796,0.00007037857,0.0002906413,0.002866954,0.0003965106,0.003121384],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005189117,"threshold_uncertainty_score":0.01735932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006308341498846236,"score_gpt":0.2082413297205273,"score_spread":0.2019329882216811,"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."}}