{"id":"W1967473444","doi":"10.1007/s10270-003-0047-5","title":"Meta-modelling and graph grammars for multi-paradigm modelling in AToM3","year":2004,"lang":"en","type":"article","venue":"Software & Systems Modeling","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":107,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Rule-based machine translation; Graph; Theoretical computer science; Programming language; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001307407,0.0005977967,0.0007108939,0.001072617,0.001162778,0.00278304,0.002146583,0.001495963,0.01016256],"category_scores_gemma":[0.002719549,0.0008520018,0.002476622,0.001170305,0.001301921,0.003720369,0.002579574,0.002397698,0.002459819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001180029,"about_ca_system_score_gemma":0.001773711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007415639,"about_ca_topic_score_gemma":0.01121093,"domain_scores_codex":[0.9988623,0.0003701266,0.0001093305,0.0001661947,0.0003726995,0.0001194557],"domain_scores_gemma":[0.9989644,0.0004498706,0.00005175752,0.0003488208,0.0001476158,0.00003745115],"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":[0.0001519899,0.00007363936,0.0004987136,0.0002351377,0.000059806,0.0003634636,0.0008401125,0.04004848,0.00565213,0.8635357,0.005201688,0.08333908],"study_design_scores_gemma":[0.00004224989,0.00003470506,0.000119608,0.00009035126,0.00008116509,0.0002512741,0.0001622682,0.2977034,0.01115762,0.6029436,0.08736154,0.00005215414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004015007,0.00006672137,0.9873664,0.0002029061,0.00004302473,0.00006568577,0.0002906967,0.002513965,0.005435572],"genre_scores_gemma":[0.1098481,0.0002067255,0.8779496,0.0001850628,0.00002909835,0.0002469553,0.001193566,0.002457771,0.007883243],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01016256,"threshold_uncertainty_score":0.03399718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1146686168020594,"score_gpt":0.2732533612831664,"score_spread":0.158584744481107,"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."}}