{"id":"W2142712680","doi":"10.1109/icde.2009.124","title":"Join Reordering by Join Simulation","year":2009,"lang":"en","type":"article","venue":"Proceedings - International Conference on Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Join (topology); Computer science; Pipeline (software); Pipeline transport; Cardinality (data modeling); Parallel computing; Path (computing); Distributed computing; Data mining; Programming language","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":[0.0002094155,0.0001889697,0.0001479003,0.000146152,0.00006639676,0.0002708272,0.001249963,0.00004642203,0.00002886638],"category_scores_gemma":[0.0002547154,0.0001924786,0.00002206665,0.0001810036,0.00001041879,0.002884918,0.0003519501,0.0001859683,0.0000291037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006294692,"about_ca_system_score_gemma":0.00002176544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007461644,"about_ca_topic_score_gemma":5.29154e-7,"domain_scores_codex":[0.9985512,0.000002837658,0.0002802522,0.0005344482,0.0003963268,0.0002349011],"domain_scores_gemma":[0.9992126,0.00003080041,0.000111774,0.000379049,0.0001828951,0.00008289118],"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":[0.00001236307,0.00004517967,0.00003983301,0.00002235486,0.00002307742,0.000004444288,0.0001646103,0.006110785,0.03189526,0.9381466,0.002773133,0.02076238],"study_design_scores_gemma":[0.0001733408,0.0000490946,0.0001499856,0.0001300285,0.000001993712,0.000008085899,0.00002458783,0.9333524,0.002480694,0.0005240348,0.06287362,0.0002321939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003521998,0.00004536091,0.9889884,0.001427479,0.0004220889,0.0001334948,0.0001294005,0.0003750796,0.004956675],"genre_scores_gemma":[0.9359511,0.00004160648,0.06321417,0.0001895199,0.0001693874,0.00000924769,0.0002454419,0.00001229714,0.000167246],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9376225,"threshold_uncertainty_score":0.7849048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05346340745751707,"score_gpt":0.3007754703162046,"score_spread":0.2473120628586875,"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."}}