{"id":"W2241447802","doi":"10.1109/ase.2015.47","title":"Semantic Slicing of Software Version Histories (T)","year":2015,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Program slicing; Slicing; Set (abstract data type); Programming language; Correctness; Java; Software engineering; Software; Software maintenance; Feature (linguistics); Software system; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005032395,0.0008601565,0.001139526,0.003270617,0.0008088193,0.002173539,0.001375999,0.0008893501,0.002266031],"category_scores_gemma":[0.02634695,0.0007268805,0.001447436,0.002495789,0.001400085,0.004717546,0.0019901,0.001088038,0.0003892857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001145013,"about_ca_system_score_gemma":0.002205737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004778253,"about_ca_topic_score_gemma":0.004695158,"domain_scores_codex":[0.9951799,0.001173426,0.0007157064,0.001089509,0.001509051,0.0003323871],"domain_scores_gemma":[0.972284,0.01237646,0.003967616,0.007419247,0.003266622,0.0006858894],"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":[0.001022998,0.0001750419,0.04239523,0.001172944,0.0002509269,0.001232278,0.002280267,0.188502,0.03596086,0.1162281,0.006567742,0.6042116],"study_design_scores_gemma":[0.00006288602,0.0003597266,0.009873016,0.000285292,0.0001367504,0.001072799,0.0006176808,0.7628851,0.06370709,0.142578,0.01830451,0.0001172338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08423538,0.0004915034,0.9067586,0.0002285736,0.0000494884,0.0002655582,0.001324297,0.004615471,0.002031191],"genre_scores_gemma":[0.4444817,0.0002938284,0.5495149,0.00009472245,0.00004267066,0.0002109387,0.003061916,0.001033817,0.001265447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005032395,"threshold_uncertainty_score":0.02661413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02676882948110706,"score_gpt":0.2551487347505602,"score_spread":0.2283799052694531,"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."}}