{"id":"W1993667152","doi":"10.1109/sera.2006.10","title":"AGADUC: Towards a More Precise Presentation of Functional Requirement in Use Case Mod","year":2006,"lang":"en","type":"article","venue":"","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Workflow; Computer science; Use Case Diagram; Ambiguity; Set (abstract data type); Natural language; Activity diagram; Process (computing); Software engineering; Programming language; Software; Unified Modeling Language; Artificial intelligence; Class diagram; Database","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":[0.01374535,0.002197222,0.001078697,0.006915886,0.001234745,0.009862579,0.003599833,0.00402146,0.007885816],"category_scores_gemma":[0.0321997,0.001961271,0.002133635,0.003776655,0.003389709,0.0128413,0.006556207,0.005155107,0.003548796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001785465,"about_ca_system_score_gemma":0.003402322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002653998,"about_ca_topic_score_gemma":0.00306681,"domain_scores_codex":[0.9885844,0.005795246,0.001184308,0.0008441873,0.003160439,0.0004314719],"domain_scores_gemma":[0.9774072,0.01262862,0.001498982,0.005108547,0.002956846,0.0003998653],"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":[0.00009579425,0.0001981894,0.001913491,0.0009997797,0.00006441026,0.001788956,0.01018382,0.018316,0.01019585,0.7421069,0.01777251,0.1963644],"study_design_scores_gemma":[0.00005532933,0.0001190842,0.0008830105,0.001035467,0.00007969225,0.003110928,0.002881114,0.126426,0.01828564,0.2507635,0.5961882,0.0001719873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00146313,0.0001050903,0.9911246,0.0004005904,0.00003677292,0.0001765713,0.00028611,0.002966519,0.003440576],"genre_scores_gemma":[0.02300472,0.0002908834,0.9714362,0.0002305941,0.00002788455,0.0004579739,0.001052127,0.0009025614,0.002597015],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01374535,"threshold_uncertainty_score":0.07269323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02585992623908412,"score_gpt":0.2595425978703574,"score_spread":0.2336826716312733,"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."}}