{"id":"W2081869633","doi":"10.1016/j.scico.2005.10.003","title":"GXL: A graph-based standard exchange format for reengineering","year":2005,"lang":"en","type":"article","venue":"Science of Computer Programming","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Interoperability; XML; Data exchange; Graph; Theoretical computer science; Programming language; Graph rewriting; Database; World Wide Web","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":[0.001268441,0.0002194791,0.0002723592,0.0005789585,0.000180701,0.0002682074,0.001882376,0.00005753991,0.000001226378],"category_scores_gemma":[0.00001173298,0.0002161459,0.0001384916,0.001217591,0.0002085394,0.001359156,0.0003640667,0.0001190068,0.000001801291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000126083,"about_ca_system_score_gemma":0.0001603659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004031963,"about_ca_topic_score_gemma":0.000001815279,"domain_scores_codex":[0.9977601,0.00001264843,0.0003797228,0.0005116184,0.0006563181,0.000679565],"domain_scores_gemma":[0.9985501,0.00006188555,0.0001413193,0.0007304491,0.0003459093,0.000170343],"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":[0.000005883787,0.00003558971,0.00003851063,0.0001197337,0.000005476063,0.000001120489,0.0003588735,0.02357721,0.0005316105,0.02990495,0.0002104476,0.9452106],"study_design_scores_gemma":[0.0003288497,0.0003395358,0.00005208621,0.0001224501,0.000003917239,0.000007108693,0.00000124817,0.8833098,0.01968342,0.00044907,0.09543341,0.0002691028],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002514629,0.000107938,0.9949697,0.0002757944,0.0003304922,0.0006170641,0.000003613409,0.001164122,0.00001662782],"genre_scores_gemma":[0.1621598,0.00000268854,0.8375256,0.00005114037,0.0001332269,0.0001054661,0.000001365435,0.00001585173,0.000004839514],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9449415,"threshold_uncertainty_score":0.8814175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01315442017528603,"score_gpt":0.2539888164817442,"score_spread":0.2408343963064582,"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."}}