{"id":"W53786381","doi":"10.1007/978-3-319-08789-4_11","title":"ChainTracker, a Model-Transformation Trace Analysis Tool for Code-Generation Environments","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Code generation; Traceability; Computer science; TRACE (psycholinguistics); Model transformation; Code (set theory); Software engineering; Transformation (genetics); Synchronizing; Systems engineering; Programming language; Engineering; Artificial intelligence; Consistency (knowledge bases); Key (lock); Computer security","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":[0.001143995,0.0005208963,0.0005903131,0.001224574,0.0002078701,0.0003718182,0.002034989,0.0003845707,0.000004438807],"category_scores_gemma":[0.00001618021,0.0005270387,0.0002724713,0.0005681986,0.000186677,0.0006836096,0.0002794649,0.0004165431,0.000007515221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003929407,"about_ca_system_score_gemma":0.0001466517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004754687,"about_ca_topic_score_gemma":0.00003367396,"domain_scores_codex":[0.9966026,0.00002540121,0.0006438651,0.001324229,0.0008656568,0.0005382571],"domain_scores_gemma":[0.997996,0.0001463878,0.0002749221,0.001347245,0.0001209301,0.000114505],"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":[0.000001862446,0.000009273768,0.000002539267,0.00001762851,0.00002465622,0.000001171671,0.0003295299,0.6278631,0.0002634965,0.05858177,0.000009222529,0.3128958],"study_design_scores_gemma":[0.0001679429,0.00009552889,0.000009371699,0.00005631425,0.00005778309,0.000005625079,7.942647e-9,0.9726672,0.003107341,0.01823677,0.005036469,0.0005596197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00005829073,0.00007270483,0.9979134,0.0003161391,0.0003854943,0.0008264463,0.00002728466,0.0003369135,0.00006330121],"genre_scores_gemma":[0.08831824,0.00004797411,0.9107474,0.0003491227,0.0002043647,0.00007742574,0.00005252279,0.00003557549,0.0001673446],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3448041,"threshold_uncertainty_score":0.9997181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01723346771089392,"score_gpt":0.2361664224659337,"score_spread":0.2189329547550398,"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."}}