{"id":"W1482671656","doi":"10.5220/0004695601740181","title":"Model Matching for Model Transformation - A Meta-heuristic Approach","year":2014,"lang":"en","type":"article","venue":"","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Transformation (genetics); Matching (statistics); Computer science; Model transformation; Heuristic; Metamodeling; Artificial intelligence; Mathematics; Statistics; 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":[0.003876833,0.001524333,0.002126552,0.003697041,0.00116204,0.002414373,0.00355437,0.002203196,0.008092953],"category_scores_gemma":[0.01442676,0.001297191,0.003983844,0.002775299,0.001327838,0.002954235,0.002670794,0.002216112,0.0009626783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002083827,"about_ca_system_score_gemma":0.003152118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006000361,"about_ca_topic_score_gemma":0.006035682,"domain_scores_codex":[0.9968728,0.001574539,0.0001896725,0.0003904958,0.0007321503,0.0002403012],"domain_scores_gemma":[0.9931177,0.005042019,0.0002754832,0.0009265851,0.0005272976,0.00011095],"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":[0.0002144524,0.0004912207,0.001466916,0.0005258808,0.000373476,0.0003223436,0.000326435,0.7390864,0.004465338,0.04978465,0.001845824,0.201097],"study_design_scores_gemma":[0.00003356824,0.00006446231,0.0001495488,0.00004901514,0.0000954105,0.00007422475,0.0000853872,0.9616672,0.001831558,0.034514,0.001417855,0.00001765072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007558517,0.0001603342,0.9880704,0.0001675371,0.00002587009,0.000213714,0.00007908641,0.0005615802,0.003162936],"genre_scores_gemma":[0.1932379,0.0002439676,0.8036372,0.0001623791,0.00002882193,0.0003470608,0.0005090614,0.0003080591,0.00152544],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008092953,"threshold_uncertainty_score":0.02707356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05905905616469243,"score_gpt":0.2577122726603643,"score_spread":0.1986532164956719,"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."}}