{"id":"W4287218407","doi":"10.5539/cis.v15n3p47","title":"Homogenous Multiple Classifier System for Software Quality Assessment Based on Support Vector Machine","year":2022,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Tertiary Education Trust Fund","keywords":"Support vector machine; Computer science; Quadratic classifier; Machine learning; Artificial intelligence; Software; AdaBoost; Classifier (UML); Linear discriminant analysis; Software quality; Data mining; Margin classifier; Confusion matrix; Random forest; Pattern recognition (psychology); Software development","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003274862,0.0001219338,0.0001909808,0.0004096391,0.001412635,0.000630418,0.001139023,0.00002428567,0.00001711106],"category_scores_gemma":[0.0001548586,0.0001061213,0.00008799626,0.001093205,0.0001423349,0.002501717,0.0006294459,0.0001765198,0.00001122667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003173579,"about_ca_system_score_gemma":0.0005469031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002433718,"about_ca_topic_score_gemma":0.000001004638,"domain_scores_codex":[0.9975651,0.0001211177,0.0004239932,0.0003565917,0.001191718,0.000341482],"domain_scores_gemma":[0.9982102,0.0005343203,0.0001530681,0.000595034,0.0003401823,0.0001672034],"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":[0.0001128166,0.0005348315,0.0293537,0.0007691295,0.00003699966,0.000006257676,0.003344754,0.1083135,0.0002155682,0.0838155,0.002170357,0.7713266],"study_design_scores_gemma":[0.0005220093,0.0003569485,0.0198133,0.000006761423,0.000002226149,0.00000728858,0.0000664541,0.9680161,0.0001130142,0.0000535048,0.01089867,0.0001436485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006179289,0.000006152532,0.9919304,0.0005161511,0.000424283,0.0003862309,0.00006655808,0.0001832168,0.000307757],"genre_scores_gemma":[0.9170816,0.000001415165,0.08169329,0.001019237,0.00002625383,0.0001233588,0.00003916066,0.000002802777,0.00001287008],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9109023,"threshold_uncertainty_score":0.9998874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03609607299771823,"score_gpt":0.3145799106342511,"score_spread":0.2784838376365328,"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."}}