{"id":"W2111585728","doi":"10.1109/se.2007.10","title":"Tracing software evolution history with design goals","year":2007,"lang":"en","type":"article","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Evolvability; Tracing; Context (archaeology); Software evolution; Software engineering; Data science; Software design; Software; History of computing; Software development; Software construction; 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":[0.01991497,0.001041417,0.0006672083,0.006325354,0.002138006,0.006195232,0.001548092,0.002569644,0.002081663],"category_scores_gemma":[0.09364513,0.002013139,0.0007774697,0.003324641,0.007428647,0.01788002,0.005582805,0.003905786,0.0005034721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006010517,"about_ca_system_score_gemma":0.00355795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003362914,"about_ca_topic_score_gemma":0.00379352,"domain_scores_codex":[0.9853254,0.008244336,0.0007572506,0.001440325,0.003666362,0.0005663011],"domain_scores_gemma":[0.9304105,0.04678703,0.005501255,0.008903203,0.007352589,0.001045523],"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":[0.0001884982,0.0002584405,0.0374877,0.0007463265,0.0001309181,0.0006138288,0.02904565,0.06523556,0.004452914,0.591605,0.002200613,0.2680344],"study_design_scores_gemma":[0.00005846572,0.0003522872,0.01034701,0.0007489402,0.0001122799,0.0005174832,0.007739233,0.1452795,0.006345626,0.7784217,0.04991334,0.0001640652],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2145894,0.002080029,0.7360032,0.007389243,0.0001044058,0.000370983,0.0001910079,0.0007297961,0.03854187],"genre_scores_gemma":[0.653369,0.001123903,0.34045,0.0003739317,0.00003860016,0.0004575612,0.0002241306,0.0004540017,0.00350876],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01991497,"threshold_uncertainty_score":0.1053217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1950393248169476,"score_gpt":0.3504107146188699,"score_spread":0.1553713898019223,"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."}}