{"id":"W4231833091","doi":"10.1109/ijcnn.2006.1716663","title":"Fuzzy Clustering of Open-Source Software Quality Data: A Case Study of Mozilla","year":2006,"lang":"en","type":"article","venue":"The 2006 IEEE International Joint Conference on Neural Network Proceedings","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Mozilla Foundation","keywords":"Computer science; Data mining; Software quality; Fuzzy logic; Software; Cluster analysis; Software metric; Ranking (information retrieval); Artificial intelligence; Software development; Operating system","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":[0.003484559,0.0004631412,0.0007137178,0.005709455,0.00167602,0.001505916,0.001324636,0.001546282,0.0003577653],"category_scores_gemma":[0.01422772,0.0002647624,0.0009401364,0.006710973,0.0009354807,0.001024858,0.001077516,0.000788258,0.0001953784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002784729,"about_ca_system_score_gemma":0.001008794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05370906,"about_ca_topic_score_gemma":0.06424449,"domain_scores_codex":[0.9972511,0.000693572,0.0001848876,0.0005290199,0.001125,0.0002164851],"domain_scores_gemma":[0.9887908,0.005713514,0.001376333,0.001275804,0.002325251,0.0005183121],"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":[0.002155382,0.001529573,0.4975295,0.001399836,0.001028064,0.01171699,0.01593325,0.1125379,0.03558334,0.008520849,0.02111472,0.2909506],"study_design_scores_gemma":[0.0002484586,0.0004668675,0.6304354,0.000236034,0.0002502937,0.003571353,0.006470879,0.3019041,0.02545743,0.005368754,0.02534929,0.0002412025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847973,0.0004584202,0.0110874,0.0006189488,0.000014859,0.0001171715,0.001261382,0.0003741222,0.001270319],"genre_scores_gemma":[0.9576973,0.0002373223,0.03582484,0.00007738439,0.00001711176,0.0001195866,0.004405203,0.0001458397,0.001475388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05370906,"threshold_uncertainty_score":0.1067929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1696753354968707,"score_gpt":0.3884468642484191,"score_spread":0.2187715287515484,"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."}}