{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005042278,0.0001706634,0.0002460802,0.0001039172,0.00007848413,0.0000985669,0.0006448496,0.00006901022,0.000001018033],"category_scores_gemma":[0.000005272188,0.0001414456,0.0001605663,0.0001010365,0.000010053,0.0006782488,0.00006097176,0.00009404802,0.00000263927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002936076,"about_ca_system_score_gemma":0.00002402249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007295946,"about_ca_topic_score_gemma":6.649079e-7,"domain_scores_codex":[0.9989845,0.00001878083,0.0002456197,0.0003033169,0.0002057749,0.0002420446],"domain_scores_gemma":[0.9992858,0.00004438095,0.00004350371,0.0004932944,0.00006471381,0.00006830901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.520118e-7,0.00001096031,5.435939e-8,0.00002667148,0.00001653534,1.458767e-8,0.0003206294,0.4876571,0.00007591035,0.508073,0.0001321454,0.003686255],"study_design_scores_gemma":[0.0001060747,0.00001760234,2.918402e-7,0.000002861287,0.00004717362,0.000002325993,5.80113e-7,0.8434645,0.0003993971,0.155332,0.0004736128,0.0001536248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001042529,0.00001148987,0.9952707,0.0001624111,0.00002572581,0.0003809707,0.000004533414,0.001542176,0.002497739],"genre_scores_gemma":[0.3061875,0.000001462882,0.6932441,0.0001381117,0.000009493267,0.0002417224,0.000005252454,0.00001367083,0.0001587332],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3558074,"threshold_uncertainty_score":0.5767984,"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."}}