{"id":"W2795868997","doi":"10.1109/saner.2018.8330192","title":"Ten years of JDeodorant: Lessons learned from the hunt for smells","year":2018,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Code refactoring; Code smell; Computer science; Java; Code (set theory); Software engineering; Source code; Software; Empirical research; Programming language; Software development; Software quality","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":[0.01390171,0.0008962841,0.0009622959,0.00552717,0.001522272,0.006969902,0.002887868,0.001777299,0.003951194],"category_scores_gemma":[0.06205356,0.0009772503,0.001182997,0.004125289,0.003422288,0.01925619,0.004393302,0.005023133,0.001915684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00198726,"about_ca_system_score_gemma":0.002574478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007023844,"about_ca_topic_score_gemma":0.01681807,"domain_scores_codex":[0.9928042,0.001594542,0.0006220727,0.001556923,0.003025535,0.0003967207],"domain_scores_gemma":[0.9223098,0.04832745,0.003251512,0.01241789,0.01094108,0.002752313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003654693,0.000375188,0.04178245,0.001656844,0.0001221836,0.0004299442,0.006890115,0.001438485,0.003735079,0.0120993,0.06607533,0.8650296],"study_design_scores_gemma":[0.00009444002,0.000549492,0.06023413,0.003016827,0.0001720367,0.001842602,0.01090814,0.008092518,0.01350113,0.04403049,0.8571787,0.0003795541],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4412,0.1419088,0.1986754,0.1211505,0.005274306,0.0004536289,0.009263743,0.01360133,0.06847244],"genre_scores_gemma":[0.492864,0.07386144,0.3646041,0.01555715,0.001840383,0.0002841069,0.01621002,0.008588595,0.0261902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01390171,"threshold_uncertainty_score":0.07352012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07313347573389459,"score_gpt":0.3282396972526515,"score_spread":0.2551062215187568,"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."}}