{"id":"W1597331078","doi":"10.5555/963600.963624","title":"A new histogram method for sparse attributes: the averaged rectangular attribute cardinality map","year":2003,"lang":"en","type":"article","venue":"Proceedings of the 1st international symposium on Information and communication technologies","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Histogram; Cardinality (data modeling); Query optimization; Oracle; Computer science; Set (abstract data type); Data mining; Algorithm; Result set; Mathematics; Pattern recognition (psychology); Artificial intelligence; Image (mathematics)","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":[0.001136158,0.0006665886,0.001053906,0.002489681,0.0005116425,0.001551006,0.001863233,0.0005140469,0.002448117],"category_scores_gemma":[0.006817547,0.0004117955,0.0005291919,0.003621568,0.0005574485,0.00299128,0.001262788,0.001066215,0.0009278017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000787583,"about_ca_system_score_gemma":0.0012584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004209427,"about_ca_topic_score_gemma":0.003112775,"domain_scores_codex":[0.9986215,0.000265735,0.00009022401,0.0002967065,0.0006360394,0.00008985521],"domain_scores_gemma":[0.9967944,0.001278845,0.0003151801,0.0006651429,0.0008106001,0.0001358074],"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":[0.0005599275,0.0001359992,0.005523273,0.0002117071,0.00009756229,0.0000648296,0.0001816713,0.08541482,0.01853552,0.01739524,0.007460327,0.8644193],"study_design_scores_gemma":[0.00006833675,0.0001875493,0.00234963,0.00001940228,0.00004279759,0.0003161771,0.0001064196,0.951269,0.02178865,0.01223536,0.01153472,0.00008202342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006681984,0.0002615607,0.9904067,0.00005538056,0.00003871975,0.00005833666,0.0001873293,0.001800382,0.0005095111],"genre_scores_gemma":[0.1460752,0.0003299078,0.8507795,0.0000874719,0.0001062956,0.0001937529,0.0007226899,0.0003755508,0.001329493],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004209427,"threshold_uncertainty_score":0.008369863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846953107407145,"score_gpt":0.2576733807892937,"score_spread":0.2392038497152223,"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."}}