{"id":"W26133019","doi":"10.1097/ede.0000000000000319","title":"Using Clustering Technique to Restructure Programs.","year":2004,"lang":"en","type":"article","venue":"Software Engineering Research and Practice","topic":"Software Engineering Research","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Restructuring; Cohesion (chemistry); Code refactoring; Computer science; Group cohesiveness; Business process reengineering; Cluster analysis; Measure (data warehouse); Software; Function (biology); Software engineering; Industrial engineering; Programming language; Database; Operations management; Business; Artificial intelligence; Engineering","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":[0.002181119,0.001161946,0.0009561759,0.005610244,0.001808049,0.001857988,0.002020207,0.001125792,0.02103529],"category_scores_gemma":[0.01415859,0.0008239151,0.00187734,0.006596609,0.0006596976,0.001485195,0.001954663,0.002275439,0.01052031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001582762,"about_ca_system_score_gemma":0.00310228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02437653,"about_ca_topic_score_gemma":0.02977037,"domain_scores_codex":[0.9977784,0.0004477527,0.0001991335,0.0006795492,0.0006756139,0.0002195875],"domain_scores_gemma":[0.9946767,0.001272821,0.0004481232,0.001816055,0.001657171,0.0001290825],"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":[0.0001712048,0.0002703762,0.00599606,0.0003955694,0.0001717078,0.0001453274,0.001190992,0.03864383,0.0105526,0.02051804,0.03482538,0.8871188],"study_design_scores_gemma":[0.0001024415,0.0002699071,0.01735039,0.0002371442,0.0002531126,0.0005540594,0.001389128,0.6303533,0.0441847,0.0708034,0.2342624,0.0002400911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0164553,0.0001867676,0.9486575,0.0003976841,0.000240192,0.0008661912,0.003182189,0.0196349,0.01037933],"genre_scores_gemma":[0.04234391,0.0001220954,0.9402304,0.0001077655,0.00003743339,0.0008722606,0.004968816,0.002268648,0.00904859],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02437653,"threshold_uncertainty_score":0.07037002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08210969072528825,"score_gpt":0.3807452638190845,"score_spread":0.2986355730937963,"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."}}