{"id":"W3090668201","doi":"10.1145/3379597.3387467","title":"On the Prevalence, Impact, and Evolution of SQL Code Smells in Data-Intensive Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Code smell; Computer science; Code refactoring; SQL; Software quality; Code review; Code (set theory); Software engineering; Software; Database; Programming language; Software development","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":[0.0003545925,0.00006057799,0.00009739868,0.00005465439,0.00001449489,0.00004647658,0.0008362928,0.00002245623,0.000007344063],"category_scores_gemma":[0.00166233,0.00003702593,0.0000110877,0.000360425,0.00003231637,0.0001847974,0.0004175391,0.0001184042,0.00001637196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004278855,"about_ca_system_score_gemma":0.00005463795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001367324,"about_ca_topic_score_gemma":0.000004451655,"domain_scores_codex":[0.9992056,0.00005740135,0.0001189653,0.000237345,0.0002431233,0.0001375676],"domain_scores_gemma":[0.9982659,0.0009945709,0.00002566252,0.0005550124,0.00010132,0.00005750466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001811798,0.0002228865,0.4237149,0.002843286,0.000228148,0.0001233126,0.009460169,0.07636071,0.01081624,0.3123449,0.1598105,0.003893692],"study_design_scores_gemma":[0.000142835,0.0001340712,0.08088537,0.00007916596,0.000001837066,0.000006274804,0.00008641212,0.9180547,0.0002893229,0.0001478403,0.000103421,0.00006875821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6110516,0.0009919188,0.3839655,0.002895499,0.0001544028,0.0005430164,0.00004713372,0.0001401952,0.000210758],"genre_scores_gemma":[0.9993897,0.00001816889,0.0004315097,0.00006808608,0.00001486115,0.000004114502,7.354944e-7,0.000003586128,0.00006925858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.841694,"threshold_uncertainty_score":0.1990085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0499365641812848,"score_gpt":0.2952276787439877,"score_spread":0.2452911145627029,"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."}}