{"id":"W2160692711","doi":"10.1109/ideas.2003.1214941","title":"Automated EJB client code generation using database query rewriting","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Rewriting; JavaBeans; Database; Programming language; SQL; Source code; Code (set theory); Software engineering; Java","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":[0.0004346982,0.000121226,0.0001270931,0.00006488895,0.00023845,0.00008294648,0.0001468122,0.0000322721,0.00002409234],"category_scores_gemma":[0.0001157735,0.0001080592,0.000028568,0.0002641985,0.0000224397,0.00124207,0.0001145514,0.00006583865,0.00002793741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005276566,"about_ca_system_score_gemma":0.00007884248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001127689,"about_ca_topic_score_gemma":0.00008995308,"domain_scores_codex":[0.9987526,0.0001220145,0.0002922675,0.0003799351,0.0001998508,0.0002533663],"domain_scores_gemma":[0.999108,0.00003435751,0.00009644009,0.0005952588,0.00008532717,0.00008062847],"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":[9.699698e-7,0.00003493804,0.0002137099,0.00002140609,0.000007668877,0.00003306403,0.0001210684,0.002569075,0.08814267,0.9052523,0.00222928,0.001373848],"study_design_scores_gemma":[0.0001858951,0.00001224099,0.00002563915,0.00004094138,0.000002960806,0.00008268992,0.00008611242,0.9185656,0.04580235,0.00005164065,0.03493604,0.00020792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03316791,0.0001060587,0.963203,0.00004433465,0.0004022981,0.0001186039,0.00002230601,0.0006512899,0.002284173],"genre_scores_gemma":[0.1556925,0.000009788414,0.8436301,0.0003004985,0.00008681371,0.000007999283,0.00004529838,0.00001064918,0.0002162957],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9159965,"threshold_uncertainty_score":0.4406528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06415247390979074,"score_gpt":0.3114656311978749,"score_spread":0.2473131572880842,"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."}}