{"id":"W2089991372","doi":"10.1109/wcre.2007.32","title":"Lossless Comparison of Nested Software Decompositions","year":2007,"lang":"en","type":"article","venue":"Proceedings - Working Conference on Reverse Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Decomposition; Lossless compression; Software; Cluster analysis; Software system; Theoretical computer science; Nested set model; Algorithm; Data mining; Distributed computing; Programming language; Data compression; Relational database; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006573893,0.0003034148,0.0003988048,0.0006184088,0.0001180073,0.0001980636,0.001112847,0.0001482645,0.00001483046],"category_scores_gemma":[0.0006716773,0.000335237,0.0000996052,0.001321802,0.00004674401,0.0003549554,0.0002585732,0.0005856897,0.00002757438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001556911,"about_ca_system_score_gemma":0.00006255525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009300313,"about_ca_topic_score_gemma":0.000001233101,"domain_scores_codex":[0.9976488,0.000005869397,0.0005089479,0.000511134,0.0006350082,0.000690208],"domain_scores_gemma":[0.9983174,0.0006095754,0.0001608645,0.0003407268,0.0003364706,0.0002349712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001308824,0.000896175,0.3552408,0.00142561,0.0003403723,0.0001392291,0.009291124,0.03249528,0.09867981,0.3976923,0.001742861,0.1019256],"study_design_scores_gemma":[0.002447808,0.0008813132,0.1728998,0.00674642,0.00008504334,0.0001613545,0.0009804892,0.6079419,0.1942524,0.001179314,0.009070804,0.003353288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2633045,0.00008256082,0.7339882,0.0001313469,0.0005334413,0.0002557207,0.000001368153,0.000991444,0.0007113659],"genre_scores_gemma":[0.8955424,0.000008347134,0.1042423,0.00002113911,0.00008823669,0.00001688771,0.000002359004,0.00003437298,0.00004392797],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6322379,"threshold_uncertainty_score":0.9999099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04362021653374086,"score_gpt":0.3034449051996365,"score_spread":0.2598246886658956,"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."}}