{"id":"W2163438246","doi":"10.14778/1687553.1687556","title":"StatAdvisor","year":2009,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); University of Waterloo","funders":"","keywords":"Computer science; IBM; Matching (statistics); SQL; Data mining; Oracle; Key (lock); Plan (archaeology); Construct (python library); Workload; Query plan; Information retrieval; Database; Statistics; Software engineering; Web search query; Mathematics; Sargable; Search engine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00264646,0.001075555,0.001113621,0.001761518,0.0005771088,0.004360562,0.004647346,0.000922018,0.05775501],"category_scores_gemma":[0.01414439,0.001519369,0.000836488,0.002141996,0.0006690609,0.003950494,0.003846236,0.002205191,0.02985708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001035483,"about_ca_system_score_gemma":0.002682291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002158446,"about_ca_topic_score_gemma":0.002656563,"domain_scores_codex":[0.9976403,0.0003300063,0.0002157658,0.0007003046,0.0009472849,0.0001664045],"domain_scores_gemma":[0.9940042,0.002268154,0.0003453553,0.002075654,0.0009519937,0.000354676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001670556,0.0001645615,0.00471972,0.001044442,0.0001120004,0.0002573548,0.000439947,0.006855211,0.006782078,0.03251711,0.4739409,0.4714961],"study_design_scores_gemma":[0.0006512353,0.0003245173,0.003276684,0.0002617885,0.00007430226,0.0006340696,0.0001676511,0.09421501,0.01324096,0.03292454,0.8541039,0.0001253358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.01199213,0.001344716,0.405017,0.001105998,0.0003892513,0.00118538,0.03839237,0.4608049,0.0797682],"genre_scores_gemma":[0.1390628,0.002057765,0.5529056,0.002090058,0.0003846507,0.002764236,0.1235071,0.07069568,0.1065322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05775501,"threshold_uncertainty_score":0.1932098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00712529554645085,"score_gpt":0.2147507865872517,"score_spread":0.2076254910408009,"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."}}