{"id":"W2014446749","doi":"10.1109/icsme.2014.108","title":"ChainTracker: Towards a Comprehensive Tool for Building Code-Generation Environments","year":2014,"lang":"en","type":"article","venue":"","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Model transformation; Computer science; Scripting language; Code generation; Model-driven architecture; Software engineering; TRACE (psycholinguistics); Transformation (genetics); Visualization; Code (set theory); Software; Programming language; Software development; Human–computer interaction; Systems engineering; Artificial intelligence; Key (lock); Engineering; Operating system","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":[0.006678832,0.002584111,0.001365213,0.004358598,0.001172299,0.005042217,0.004312955,0.00297674,0.01771399],"category_scores_gemma":[0.0234389,0.002548194,0.002180166,0.002774346,0.001464996,0.007888006,0.005807015,0.004937791,0.009596006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222376,"about_ca_system_score_gemma":0.004215618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003531164,"about_ca_topic_score_gemma":0.004074514,"domain_scores_codex":[0.9961196,0.0007666809,0.0005297001,0.0006760047,0.001693757,0.000214212],"domain_scores_gemma":[0.9880034,0.00672445,0.0007295,0.002178619,0.00178911,0.0005749936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008526776,0.0004791502,0.005249911,0.002262257,0.00026383,0.001131446,0.002543931,0.03865051,0.025436,0.05312961,0.1208465,0.7491542],"study_design_scores_gemma":[0.0004958751,0.0003145344,0.001548253,0.001100138,0.0001874884,0.001215581,0.0004245526,0.4635695,0.07034852,0.1010227,0.3593618,0.0004110897],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00106047,0.0001287936,0.8659295,0.0001439236,0.00006038897,0.0001477444,0.0008278558,0.1304751,0.001226179],"genre_scores_gemma":[0.02079775,0.0005820858,0.9415846,0.0002309133,0.00004879288,0.0005360818,0.005128397,0.02675198,0.004339429],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01771399,"threshold_uncertainty_score":0.05925924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02577405965568058,"score_gpt":0.2562543681221741,"score_spread":0.2304803084664935,"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."}}