{"id":"W1631202982","doi":"10.1109/compsac.2015.256","title":"Adaptive Clustering Techniques for Software Components and Architecture","year":2015,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cluster analysis; Computer science; Data mining; Fuzzy clustering; FLAME clustering; Hierarchical clustering; Metric (unit); Software metric; Software; Component (thermodynamics); Correlation clustering; CURE data clustering algorithm; Artificial intelligence; Software system; Software construction; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002369635,0.00009282374,0.0000991881,0.0001026039,0.00004149141,0.00008669945,0.0003936188,0.00004274993,8.586542e-7],"category_scores_gemma":[0.0003365915,0.00007944468,0.00002075566,0.0001206098,0.00002650784,0.0001581865,0.000401872,0.00009636033,0.000003457022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003769961,"about_ca_system_score_gemma":0.00002976191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002546766,"about_ca_topic_score_gemma":0.000005417151,"domain_scores_codex":[0.9992468,0.00001561517,0.00008178458,0.0002433163,0.0001899868,0.0002225046],"domain_scores_gemma":[0.9991239,0.0003667213,0.00001464889,0.0002524976,0.00009472532,0.0001475181],"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":[0.00009166457,0.00008347654,0.006402862,0.000144204,0.00006490779,0.00003013837,0.002684165,0.002043384,0.00186313,0.006476834,0.005887958,0.9742272],"study_design_scores_gemma":[0.00371711,0.002869103,0.01930446,0.0003490648,0.0000181099,0.0004413868,0.0001887306,0.7672363,0.03788796,0.05109669,0.1146922,0.002198921],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002941396,0.00006887698,0.9954443,0.0002522127,0.00008505311,0.0002829182,0.000002127123,0.000806228,0.0001168941],"genre_scores_gemma":[0.1781631,0.000001245899,0.8214943,0.00007279207,0.00003943559,0.00005428154,0.000001195964,0.00001055561,0.0001630383],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9720284,"threshold_uncertainty_score":0.323966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04937350249887535,"score_gpt":0.2831740470574781,"score_spread":0.2338005445586028,"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."}}