{"id":"W2988126082","doi":"10.1109/vissoft.2019.00019","title":"CloneCompass: Visualizations for Exploring Assembly Code Clone Ecosystems","year":2019,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; clone (Java method); Source code; Code (set theory); Codebase; Software engineering; Software; Function (biology); Visualization; Process (computing); Programming language; Data mining","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":[0.001783504,0.001191263,0.0004277289,0.003791295,0.0006987297,0.002202447,0.001053862,0.001008774,0.01338114],"category_scores_gemma":[0.01031782,0.0005774937,0.0007246362,0.001658823,0.0004990829,0.002748502,0.002814193,0.0009921234,0.001218888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005680296,"about_ca_system_score_gemma":0.0008179246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002932204,"about_ca_topic_score_gemma":0.005076994,"domain_scores_codex":[0.9994863,0.0001729718,0.00004177037,0.00008585433,0.0001702818,0.00004279095],"domain_scores_gemma":[0.9931976,0.004878808,0.0003856893,0.0005725112,0.0007172063,0.0002481544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002360788,0.0006213472,0.02571747,0.003762292,0.0003219654,0.002937782,0.03839204,0.04186194,0.110182,0.06247635,0.1148963,0.5964698],"study_design_scores_gemma":[0.000562322,0.0007880547,0.02821029,0.001219165,0.0002230778,0.002570463,0.007621957,0.528572,0.09088943,0.06804139,0.2707883,0.000513607],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1164945,0.0007757474,0.7808136,0.001319286,0.0001648744,0.0005440567,0.009362656,0.07811169,0.01241357],"genre_scores_gemma":[0.3225635,0.0006003719,0.6611165,0.000223273,0.00005189083,0.0008664298,0.004652913,0.006623989,0.003301076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01338114,"threshold_uncertainty_score":0.04476434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07011543209215279,"score_gpt":0.317883732952852,"score_spread":0.2477683008606993,"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."}}