{"id":"W2147555693","doi":"10.1109/wcre.1995.514698","title":"Pattern matching for design concept localization","year":2002,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Programming language; Code generation; Compiler; Source code; KPI-driven code analysis; Code (set theory); Redundant code; Software visualization; Matching (statistics); Reverse engineering; Fragment (logic); Static program analysis; Software development; Software; Theoretical computer science; Key (lock); Software construction","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":[0.0001319715,0.00004979418,0.00004798948,0.00004430721,0.00004871914,0.00009621525,0.0003387204,0.00002349991,0.00008589754],"category_scores_gemma":[0.0001124218,0.00004547439,0.00001826297,0.0001387613,0.000007937501,0.0001947092,0.00005375222,0.00003584245,0.00006856696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002282223,"about_ca_system_score_gemma":0.000005233013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009891532,"about_ca_topic_score_gemma":3.815792e-7,"domain_scores_codex":[0.9994463,0.00001725573,0.00007297528,0.0001543378,0.0001396218,0.000169504],"domain_scores_gemma":[0.9992012,0.0004994175,0.00001034608,0.0002039043,0.00004290748,0.00004217987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001875041,0.00008844056,0.002163508,0.00005822595,0.00002676721,0.00001384633,0.00440455,0.2187018,0.0004021314,0.01810013,0.08264068,0.6733981],"study_design_scores_gemma":[0.0001393452,0.00003499789,0.0001585329,0.000005739153,4.858078e-7,0.000002656239,0.000004633937,0.9958112,0.001772757,0.0007943934,0.001203457,0.00007186684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001531373,0.00004660152,0.9988135,0.0002804986,0.0001234932,0.0001635035,3.387855e-7,0.0003373835,0.00008151195],"genre_scores_gemma":[0.7517686,0.000002621661,0.2470729,0.0002851155,0.00004806662,0.00003265976,8.15845e-7,0.00001004933,0.0007792206],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7771093,"threshold_uncertainty_score":0.1854392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04744163885835213,"score_gpt":0.2684536603072659,"score_spread":0.2210120214489138,"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."}}