{"id":"W1902003010","doi":"10.1002/smr.1696","title":"A selection of distinguished papers from the 19th Working Conference on Reverse Engineering 2012","year":2014,"lang":"en","type":"article","venue":"Journal of Software Evolution and Process","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reverse engineering; Computer science; Program slicing; Variety (cybernetics); Slicing; Selection (genetic algorithm); Java; Software engineering; Source code; Quality (philosophy); Data science; World Wide Web; Programming language; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008634128,0.002550726,0.002571902,0.01252733,0.002838125,0.01041523,0.002243203,0.002932684,0.08803973],"category_scores_gemma":[0.01937021,0.0009049109,0.002352334,0.0102964,0.001008191,0.00621937,0.00474032,0.0047582,0.05481219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003619979,"about_ca_system_score_gemma":0.004714566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001279864,"about_ca_topic_score_gemma":0.002494727,"domain_scores_codex":[0.9923958,0.0008186241,0.0006356015,0.000998046,0.004415696,0.0007362514],"domain_scores_gemma":[0.9669543,0.00444727,0.00140611,0.001695791,0.01925754,0.006239063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009611557,0.00005531104,0.0001878871,0.000558997,0.00002251716,0.00009318996,0.00007562646,0.0002240368,0.001285423,0.002053174,0.8646935,0.1306542],"study_design_scores_gemma":[0.00002359081,0.00007146849,0.0005642013,0.0004950893,0.00002164912,0.0001692961,0.0001031473,0.0002506528,0.0007235622,0.002203848,0.9953411,0.00003254787],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.003230689,0.1237714,0.04614769,0.06090917,0.6659358,0.001050574,0.004372132,0.002144814,0.09243768],"genre_scores_gemma":[0.0141738,0.1192434,0.03010866,0.01265182,0.2698858,0.001306269,0.01804684,0.005218727,0.5293646],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.08803973,"threshold_uncertainty_score":0.2945222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01548924074106418,"score_gpt":0.2419680855059589,"score_spread":0.2264788447648947,"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."}}