{"id":"W2134092469","doi":"10.1002/spe.386","title":"Shimba—an environment for reverse engineering Java software systems","year":2001,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Software Engineering Research","field":"Computer Science","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Academy of Finland; Association of Canadian Universities for Research in Astronomy; Nokia","keywords":"Computer science; Reverse engineering; Java; Sequence diagram; Software; Programming language; Abstraction; TRACE (psycholinguistics); Sequence (biology); Software system; Software engineering; Unified Modeling Language","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006293252,0.0002786602,0.0002400901,0.0001406196,0.0002637273,0.0004668399,0.0008611142,0.0001247308,0.00001479788],"category_scores_gemma":[0.005408206,0.0002863611,0.00005520805,0.0003060726,0.00006555687,0.003126214,0.0003333469,0.000262344,0.00004653382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00012431,"about_ca_system_score_gemma":0.00006488321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001167194,"about_ca_topic_score_gemma":0.000001042089,"domain_scores_codex":[0.9976249,0.00006230558,0.0003033334,0.0007976277,0.0005429134,0.0006689281],"domain_scores_gemma":[0.9961308,0.002341372,0.0001038268,0.0009350247,0.0001251345,0.0003638391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001073601,0.002923142,0.09598497,0.002455202,0.0006993835,0.003105016,0.1442076,0.1222615,0.008933681,0.02960224,0.01221987,0.5765338],"study_design_scores_gemma":[0.001235371,0.0008462768,0.004115984,0.0001893444,0.0000401076,0.001343922,0.002794752,0.04495791,0.0007955799,0.0001438633,0.9420429,0.00149393],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0398596,0.001340057,0.9565952,0.0003456143,0.0005770798,0.0005019114,0.000005496397,0.0007637427,0.00001132589],"genre_scores_gemma":[0.28496,0.0007720547,0.7121184,0.0004386851,0.0003181225,0.0008506278,0.00001168603,0.00007732261,0.0004531123],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9298231,"threshold_uncertainty_score":0.9999589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02269407837112575,"score_gpt":0.2825363977862558,"score_spread":0.25984231941513,"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."}}