{"id":"W2103640219","doi":"10.1109/tse.2005.28","title":"Using origin analysis to detect merging and splitting of source code entities","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Software Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":252,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Context (archaeology); Source code; Code (set theory); Abstraction; Programming language; Software; Plan (archaeology); Software evolution; Software engineering; Database; Theoretical computer science; Software system; Data mining; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003312276,0.0002236137,0.0003169666,0.001217352,0.0001262018,0.0001039702,0.0004010737,0.00007153267,0.00001414179],"category_scores_gemma":[0.0001323858,0.0002581778,0.0001467759,0.001860196,0.00002202592,0.0003799341,0.00001306029,0.0002773675,0.0000067409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001566904,"about_ca_system_score_gemma":0.00003587157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000609678,"about_ca_topic_score_gemma":0.00001527005,"domain_scores_codex":[0.9984098,0.00002282948,0.0003244874,0.0004177325,0.0004029805,0.0004221658],"domain_scores_gemma":[0.9985125,0.0006919536,0.00004464104,0.0004801021,0.0000849038,0.0001858873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002478161,0.00001242016,0.0005504718,0.00004268955,0.0001988948,0.000002664983,0.0005367385,0.968383,0.004313224,0.00001857154,0.000002525557,0.0259363],"study_design_scores_gemma":[0.0001992153,0.00004863205,0.001306963,0.00009490536,0.0001158659,0.00001695791,0.00002538436,0.928861,0.06841882,0.000002805272,0.0005573595,0.0003520689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2959569,0.00009147241,0.7032263,0.00001747598,0.0001472773,0.00009088404,0.000006642297,0.0004616024,0.000001407723],"genre_scores_gemma":[0.6600162,0.000008113235,0.3398435,0.00001263584,0.00003187015,0.00001305341,2.290132e-7,0.00002514356,0.00004931987],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3640593,"threshold_uncertainty_score":0.9999871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02389376451113013,"score_gpt":0.2743728504647013,"score_spread":0.2504790859535712,"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."}}