{"id":"W4240377892","doi":"10.1109/icws.2004.1314752","title":"Designing Web services with Tropos","year":2004,"lang":"en","type":"article","venue":"Proceedings. IEEE International Conference on Web Services, 2004.","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Software engineering; Design methods; Web service; Web design; World Wide Web; Systems engineering; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002977461,0.0003917221,0.0002906369,0.0003370424,0.0002242954,0.0009630755,0.001888559,0.0001432693,0.00009026503],"category_scores_gemma":[0.000005561395,0.0003315304,0.00007670074,0.0004181483,0.00003705729,0.001894895,0.0001217027,0.0002916746,0.0004626293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002647133,"about_ca_system_score_gemma":0.0002639274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002962848,"about_ca_topic_score_gemma":0.0002847021,"domain_scores_codex":[0.997144,0.00001734561,0.0004792862,0.0008289861,0.001083815,0.0004465517],"domain_scores_gemma":[0.99808,0.00001981916,0.000473089,0.0002617324,0.0009699456,0.0001954731],"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":[0.0004922558,0.001217537,0.02996831,0.001497983,0.0006031026,0.0001133296,0.01199558,0.002825727,0.4723271,0.4736626,0.0007196461,0.004576805],"study_design_scores_gemma":[0.008697956,0.001303088,0.005372376,0.00495927,0.00008012596,0.0002876008,0.002657157,0.8714147,0.08660802,0.0084067,0.007840782,0.002372219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8915029,0.0001309605,0.03924673,0.004997644,0.002406471,0.001108102,0.00003933048,0.001048649,0.05951919],"genre_scores_gemma":[0.984021,0.00005491309,0.01390524,0.001123899,0.0003694132,0.00007332505,0.00001908389,0.00003052379,0.0004026059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.868589,"threshold_uncertainty_score":0.9999137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03232167338817918,"score_gpt":0.2670655532372669,"score_spread":0.2347438798490877,"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."}}