{"id":"W2049244577","doi":"10.1007/s10270-013-0370-4","title":"T-Core: a framework for custom-built model transformation engines","year":2013,"lang":"en","type":"article","venue":"Software & Systems Modeling","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Transformation (genetics); Model transformation; Reuse; Programming language; Context (archaeology); Program transformation; Task (project management); Software engineering; Model-driven architecture; Theoretical computer science; Unified Modeling Language; Systems engineering; Artificial intelligence; Engineering; Software","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":[0.001977888,0.001899907,0.001085947,0.001698078,0.0006677413,0.003060209,0.004409738,0.001544542,0.02059212],"category_scores_gemma":[0.006333746,0.001652246,0.00326019,0.001282029,0.0009433225,0.00441961,0.003602918,0.003294155,0.008761052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001029628,"about_ca_system_score_gemma":0.001945298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004033951,"about_ca_topic_score_gemma":0.006110751,"domain_scores_codex":[0.9989468,0.0001867553,0.0001347798,0.0002218216,0.0003879364,0.0001218383],"domain_scores_gemma":[0.9977914,0.0007642496,0.0001121797,0.0008971741,0.0003266001,0.0001084265],"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":[0.001008272,0.0005660038,0.004237222,0.00257381,0.0008609752,0.001360681,0.0009684503,0.09982897,0.03958092,0.1978339,0.1430147,0.5081662],"study_design_scores_gemma":[0.0002141208,0.000121691,0.0006433815,0.0003235493,0.0002492667,0.0007867765,0.000132086,0.6247789,0.05731535,0.1012261,0.2140088,0.0002000002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001178594,0.0000684616,0.9257858,0.00005076555,0.00005582038,0.0001240393,0.0007027658,0.06973732,0.002296455],"genre_scores_gemma":[0.07469521,0.000609944,0.8568285,0.0003755171,0.00007112013,0.0007022478,0.009226086,0.04851355,0.008977844],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02059212,"threshold_uncertainty_score":0.06888753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05798736777553443,"score_gpt":0.2826800733855033,"score_spread":0.2246927056099689,"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."}}