{"id":"W3212368723","doi":"10.3390/modelling2040032","title":"Generation of Custom Textual Model Editors","year":2021,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Personalization; Code generation; Domain (mathematical analysis); Software engineering; Architecture; Text generation; Formalism (music); Programming language; Software; Model-driven architecture; World Wide Web; Artificial intelligence; Software development; Key (lock)","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":[0.002833553,0.0009574422,0.0005197681,0.001125355,0.0003903515,0.001900818,0.001886109,0.001099815,0.01121304],"category_scores_gemma":[0.01224825,0.0008326886,0.001136654,0.0004939982,0.0005382592,0.00241524,0.00240786,0.001470594,0.003918682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005597314,"about_ca_system_score_gemma":0.0008023129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004764137,"about_ca_topic_score_gemma":0.0007894111,"domain_scores_codex":[0.9987072,0.0002709614,0.0001791229,0.0002544695,0.0005255291,0.00006273252],"domain_scores_gemma":[0.9914182,0.003080648,0.0004274567,0.003032546,0.001806399,0.0002347202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008222082,0.0008191073,0.005336329,0.002551967,0.0002963906,0.003398701,0.004235052,0.1000848,0.2191988,0.1634262,0.09906564,0.4007649],"study_design_scores_gemma":[0.000276427,0.0001527641,0.0006855447,0.0001968035,0.0001709676,0.0009098315,0.0002582004,0.5114664,0.1539084,0.02594631,0.3058962,0.0001321486],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01437739,0.00007785264,0.9400026,0.0002395888,0.0003213766,0.0003478228,0.001911688,0.0333922,0.009329568],"genre_scores_gemma":[0.1394597,0.0002778261,0.8170621,0.0002875238,0.0001052679,0.0007247537,0.008119454,0.01467394,0.01928938],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01121304,"threshold_uncertainty_score":0.03751135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1047785751101621,"score_gpt":0.3514389269889763,"score_spread":0.2466603518788142,"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."}}