{"id":"W1985364899","doi":"10.1007/11880240_18","title":"Semantic Variations Among UML StateMachines","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Software Engineering Research","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Semantics (computer science); Programming language; Unified Modeling Language; Operational semantics; Formal semantics (linguistics); Software","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":[0.003099293,0.0008558097,0.0006627656,0.002591063,0.001231043,0.004045827,0.001639352,0.001487086,0.003716027],"category_scores_gemma":[0.008566054,0.001397712,0.001358693,0.0030459,0.002493542,0.008358944,0.002829588,0.002566661,0.001103659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001678733,"about_ca_system_score_gemma":0.0009766606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001490684,"about_ca_topic_score_gemma":0.00210428,"domain_scores_codex":[0.9955125,0.00148204,0.0004869352,0.000659969,0.001612796,0.0002456889],"domain_scores_gemma":[0.9957016,0.002211382,0.0002968491,0.001158596,0.0005447137,0.00008684215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000068118,0.00003133462,0.0004243719,0.000129949,0.00002210418,0.0002566935,0.001578864,0.004461152,0.004501797,0.8993998,0.002375287,0.08675061],"study_design_scores_gemma":[0.00002099543,0.00003956636,0.0004862477,0.0001949695,0.0001051291,0.0004648274,0.0003016076,0.04675126,0.01651395,0.8401945,0.09486789,0.000059076],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02706055,0.0006621009,0.9477716,0.0005021161,0.0002434994,0.0001101812,0.0004823071,0.004480007,0.01868755],"genre_scores_gemma":[0.4831551,0.0009836574,0.4985074,0.0003055871,0.0002060645,0.0002420355,0.001654268,0.00313019,0.01181568],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004045827,"threshold_uncertainty_score":0.0163908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204624036319042,"score_gpt":0.2510508787834189,"score_spread":0.2390046384202284,"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."}}