{"id":"W2118067603","doi":"10.1109/isorcw.2011.18","title":"Product Model Derivation by Model Transformation in Software Product Lines","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Model transformation; Computer science; Unified Modeling Language; Metamodeling; Feature model; Software product line; Programming language; Software engineering; Applications of UML; Feature (linguistics); Model-driven architecture; Transformation (genetics); Software; Data mining; Software development; 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":[0.0004330427,0.0001635388,0.0001571949,0.0001408352,0.0000421664,0.00002634794,0.000503049,0.00004498756,0.000001691341],"category_scores_gemma":[0.0004823864,0.0001477159,0.00002908284,0.000370042,0.00002321329,0.001805513,0.00006595528,0.0001364908,0.000005224383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004913917,"about_ca_system_score_gemma":0.00005381797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001413895,"about_ca_topic_score_gemma":0.000006290411,"domain_scores_codex":[0.9988263,0.00003921484,0.0002913371,0.000405585,0.0001765694,0.0002610076],"domain_scores_gemma":[0.9992775,0.00005510342,0.00005348734,0.0004838374,0.00009252538,0.00003751817],"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":[0.000006366767,0.0000448249,0.00009450422,0.00003518495,0.000002800432,4.444964e-7,0.00313104,0.9475805,0.003535934,0.005195998,0.0002036404,0.04016873],"study_design_scores_gemma":[0.0001282931,0.00001686147,0.0001756247,0.00001076905,0.000001559915,0.000002459747,0.00001073266,0.8817709,0.06740247,0.05026192,0.0000171072,0.0002013208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01050722,0.0001126838,0.9875579,0.0002523601,0.000114122,0.0003020404,0.000001995499,0.0009680942,0.0001835979],"genre_scores_gemma":[0.2067848,0.00002178602,0.7928647,0.00006477276,0.00001237886,0.00004953289,0.000005385073,0.00001172167,0.0001848297],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1962776,"threshold_uncertainty_score":0.6023681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08627151491766138,"score_gpt":0.2773887662957811,"score_spread":0.1911172513781197,"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."}}