{"id":"W2033239109","doi":"10.1145/1101908.1101941","title":"Visualization-based analysis of quality for large-scale software systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer science; Visualization; Software visualization; Software quality; Data science; Software evolution; Software; Software development; Software system; Quality (philosophy); Software analytics; Software metric; Software engineering; Visual analytics; Data visualization; Creative visualization; Scale (ratio); Data mining; Software construction","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008993447,0.00008279632,0.0002527447,0.0003913771,0.00004905857,0.00006593493,0.0005339623,0.0000510133,0.00003021736],"category_scores_gemma":[0.0007382294,0.00007605628,0.0001448558,0.001619653,0.00001119208,0.0001592221,0.00006318873,0.00003599939,0.000007328567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005836829,"about_ca_system_score_gemma":0.00007344536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006436503,"about_ca_topic_score_gemma":0.0000641492,"domain_scores_codex":[0.998726,0.00005365597,0.0003132758,0.000269062,0.0003955331,0.000242485],"domain_scores_gemma":[0.9974652,0.001481118,0.00006892036,0.0005803793,0.0003289932,0.00007537838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001172994,0.0003459035,0.2156909,0.000310349,0.0004879977,4.926533e-7,0.0005997833,0.710653,0.0002451641,0.06649484,0.001970657,0.00318912],"study_design_scores_gemma":[0.0002421954,0.00002360064,0.02613836,0.000006693648,0.00003100609,7.797254e-8,0.00001481657,0.9704429,0.001219222,0.00001363157,0.001768704,0.00009880067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01595637,0.00006944618,0.9831937,0.0001194446,0.0000784368,0.0001973027,0.00002940474,0.0003307714,0.00002515373],"genre_scores_gemma":[0.8326895,7.415296e-7,0.1667414,0.00008331514,0.00003376486,0.00005246815,0.00002910619,0.000008985279,0.0003606764],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8167331,"threshold_uncertainty_score":0.3101485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02772441894804635,"score_gpt":0.3403517475959456,"score_spread":0.3126273286478993,"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."}}