{"id":"W2463570186","doi":"","title":"The pervasiveness of global data in evolving software systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Leverage (statistics); Code refactoring; Software; Software development; Software evolution; Software system; Data science; Software engineering; Software metric; Software construction; Artificial intelligence; Programming language","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":[0.01108415,0.0002357792,0.0004124341,0.003246121,0.005899609,0.01372335,0.0014229,0.002426452,0.003646302],"category_scores_gemma":[0.05374235,0.0008233426,0.0003619998,0.002727093,0.02579126,0.03306843,0.01142537,0.004394003,0.0002814933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002708261,"about_ca_system_score_gemma":0.003160302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004174575,"about_ca_topic_score_gemma":0.00432704,"domain_scores_codex":[0.991581,0.004509443,0.0005065101,0.001177554,0.001592146,0.0006333822],"domain_scores_gemma":[0.957958,0.02807493,0.00335979,0.006942306,0.002513014,0.001151935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006164503,0.00001991565,0.008483508,0.00009134156,0.00001563946,0.0005631133,0.141282,0.0006608166,0.001086313,0.8160818,0.0009105404,0.03074333],"study_design_scores_gemma":[0.00002686368,0.000082589,0.01113849,0.0004919181,0.00007908751,0.001865046,0.1891167,0.008009585,0.004241647,0.6250726,0.1598014,0.0000741134],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.632329,0.002541346,0.1752837,0.02045839,0.000393946,0.00009870581,0.0002172149,0.00026834,0.1684093],"genre_scores_gemma":[0.9918048,0.0002722903,0.00501266,0.0002180735,0.00005338824,0.00001782367,0.00003414613,0.00006777415,0.002519027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01372335,"threshold_uncertainty_score":0.05861932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04012145216912319,"score_gpt":0.2569127109457115,"score_spread":0.2167912587765883,"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."}}