{"id":"W2163689760","doi":"10.1109/wcre.2004.37","title":"The small world of software reverse engineering","year":2005,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Reverse engineering; Business process reengineering; Computer science; Software engineering; Data science; Social software engineering; Software maintenance; Software; Software development; Software construction; Engineering; Programming language; Manufacturing 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":[0.004923405,0.0004929871,0.0007843378,0.004435677,0.003831033,0.01086757,0.001293863,0.002602652,0.01377546],"category_scores_gemma":[0.03405626,0.0005431069,0.0005591715,0.005118712,0.008107768,0.02235099,0.004632705,0.003535606,0.003019215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173738,"about_ca_system_score_gemma":0.001944105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001204869,"about_ca_topic_score_gemma":0.001739216,"domain_scores_codex":[0.9962287,0.001885499,0.00009258281,0.0006809648,0.0009425394,0.0001696982],"domain_scores_gemma":[0.9421811,0.04514998,0.003121872,0.005459809,0.002282235,0.001805087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000261077,0.00011533,0.007011408,0.0008048092,0.000115792,0.001503147,0.004936396,0.003228754,0.001881915,0.6180773,0.0723092,0.2897549],"study_design_scores_gemma":[0.00003180874,0.00008356894,0.003747821,0.0003722235,0.00003874622,0.001237078,0.004232639,0.004008378,0.0008384606,0.6210068,0.3643505,0.00005180908],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2211722,0.0618582,0.1828614,0.2090351,0.003507604,0.0002289135,0.001809836,0.001868459,0.3176582],"genre_scores_gemma":[0.859556,0.03370718,0.05349853,0.01098191,0.004751114,0.0003460622,0.001124937,0.0008509497,0.03518342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01377546,"threshold_uncertainty_score":0.04608351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0147984732450518,"score_gpt":0.2269586229086818,"score_spread":0.21216014966363,"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."}}