{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003202313,0.00007211258,0.0000725125,0.00009956664,0.00004536409,0.00005606401,0.0009292719,0.00001902167,0.00001724595],"category_scores_gemma":[0.0006367406,0.00005115008,0.00004188814,0.0004772758,0.00001830581,0.0001371692,0.0002429761,0.0001279454,0.00005696609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003754825,"about_ca_system_score_gemma":0.0000320594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001442797,"about_ca_topic_score_gemma":0.00003395318,"domain_scores_codex":[0.999248,0.000009828869,0.0001379802,0.000143736,0.0002107764,0.000249662],"domain_scores_gemma":[0.9982274,0.001078535,0.00001901447,0.0005519922,0.00006103753,0.00006203488],"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":[0.00001158937,0.0001191014,0.02441824,0.0001347725,0.0001167975,0.00002756045,0.0008963611,0.08496071,0.002478779,0.1346494,0.04011757,0.7120691],"study_design_scores_gemma":[0.0005091327,0.00006878775,0.03596717,0.0000835883,0.000005119141,0.00002240899,0.00001419052,0.2319528,0.03094377,0.0003189072,0.6996256,0.0004884677],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009315969,0.0002402091,0.988157,0.001155321,0.000195902,0.00009043045,3.691061e-7,0.0004726195,0.0003722325],"genre_scores_gemma":[0.3648686,0.00001976044,0.6270068,0.0001027705,0.0001249516,0.00001699163,2.919573e-7,0.0000175178,0.00784232],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7115806,"threshold_uncertainty_score":0.208584,"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."}}