{"id":"W1975343474","doi":"10.1145/1176617.1176701","title":"Round-trip engineering of eclipse plug-ins using eclipse workbench part interaction FSML","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Eclipse; Workbench; Computer science; Software engineering; Plug-in; Programming language; Domain (mathematical analysis); Modeling language; Model-driven architecture; Software development; Systems engineering; Software; Engineering; Artificial intelligence","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":[0.0004325439,0.0002230002,0.0002972463,0.0002463312,0.0000573107,0.00007996452,0.0005284259,0.00009851185,0.00002669318],"category_scores_gemma":[0.0004132074,0.0002207209,0.0001025603,0.0006195354,0.00002898582,0.001012916,0.0002303589,0.0002260335,0.00001134583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001529251,"about_ca_system_score_gemma":0.00003700432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008267051,"about_ca_topic_score_gemma":0.00001068585,"domain_scores_codex":[0.9984825,0.00006126925,0.0004500512,0.0003854547,0.0002470928,0.0003736183],"domain_scores_gemma":[0.9983802,0.0007249914,0.0001482212,0.0005997109,0.00009012621,0.00005673658],"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":[0.000004244143,0.00003709482,0.0004079865,0.00002980128,0.0000151263,0.000009348129,0.00008893946,0.9767933,0.003942717,0.01417412,0.000309963,0.004187374],"study_design_scores_gemma":[0.0008562685,0.0001646133,0.003097762,0.0003600096,0.00004372885,0.0001476497,0.0001153648,0.8725169,0.08197629,0.02286272,0.01651487,0.001343836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07108697,0.00009129856,0.9252769,0.00003724204,0.002299431,0.0001028622,0.000001183846,0.0005562289,0.000547823],"genre_scores_gemma":[0.1871022,0.00001069725,0.8115563,0.00001900183,0.0009734225,0.000007659284,0.000002329393,0.00002100659,0.0003072814],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1160153,"threshold_uncertainty_score":0.9000739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04661667051225226,"score_gpt":0.2826360061058348,"score_spread":0.2360193355935825,"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."}}