{"id":"W2743326897","doi":"10.1109/qrs.2017.41","title":"Predicting Fault-Prone Classes in Object-Oriented Software: An Adaptation of an Unsupervised Hybrid SOM Algorithm","year":2017,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science; Machine learning; Data mining; Artificial intelligence; Software fault tolerance; Software quality; Software system; Adaptation (eye); Software metric; Source code; Software; Algorithm; Software development; 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":[0.00165699,0.001174826,0.001201072,0.002462314,0.0005370122,0.0008024051,0.002261596,0.001280222,0.001031757],"category_scores_gemma":[0.003010551,0.0004654907,0.001492962,0.001962222,0.0004192077,0.001141111,0.0009003742,0.001006256,0.0006093714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006309316,"about_ca_system_score_gemma":0.001010145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01292817,"about_ca_topic_score_gemma":0.01504946,"domain_scores_codex":[0.9993417,0.0001338904,0.00005479022,0.0002053737,0.0001710829,0.00009319463],"domain_scores_gemma":[0.9985248,0.0005698759,0.0001142707,0.0001557905,0.0005574589,0.0000777542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000333905,0.0004551446,0.01303339,0.0001361697,0.0003907261,0.0001402569,0.0001285283,0.4071574,0.003785675,0.001144004,0.003264709,0.5700301],"study_design_scores_gemma":[0.000008755514,0.00002369957,0.000703712,0.000007054872,0.00001320451,0.0000190022,0.00001445135,0.9977096,0.0006001653,0.0006935123,0.0002009924,0.000005847396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1125025,0.0006747372,0.8792129,0.0002724361,0.0001396607,0.0002178323,0.0004983721,0.004215043,0.002266567],"genre_scores_gemma":[0.5441583,0.0003715137,0.4495124,0.000264327,0.0001252509,0.0003088449,0.0016465,0.000250823,0.003361874],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01292817,"threshold_uncertainty_score":0.02570587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02652344047027128,"score_gpt":0.285626669439664,"score_spread":0.2591032289693928,"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."}}