{"id":"W2566585724","doi":"10.1080/09398368.2000.11463471","title":"Multi Agent-Aided Tools for Engineering System Design: A Case Study","year":2000,"lang":"en","type":"article","venue":"EPE Journal","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Process (computing); Key (lock); Architecture; Simple (philosophy); Multi-agent system; Java; Multidisciplinary approach; Systems engineering; Engineering design process; Expert system; Software engineering; Artificial intelligence; Knowledge management; Engineering; Computer security","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":[0.0009878213,0.0001310139,0.0001833945,0.00009884313,0.0002693969,0.0005611427,0.0003155952,0.00004126,0.00002789976],"category_scores_gemma":[0.00004867272,0.0001106123,0.00009527352,0.0001344438,0.000002675236,0.0007448444,0.00002426292,0.0001291873,0.00004443068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001225961,"about_ca_system_score_gemma":0.00004154981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003588018,"about_ca_topic_score_gemma":0.000005818767,"domain_scores_codex":[0.998781,0.0001243131,0.000404111,0.0002041195,0.0002290904,0.0002573591],"domain_scores_gemma":[0.9992577,0.0001423547,0.000130748,0.000247351,0.00007845351,0.0001433479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001927025,0.002648701,0.003103796,0.0006482045,0.001087869,0.04304878,0.06012719,0.2267144,0.01518672,0.001271735,0.009972339,0.6359976],"study_design_scores_gemma":[0.001972615,0.0002410919,0.001065093,0.00008474922,0.0000211588,0.01217837,0.000880716,0.9812027,0.000260857,0.000001862083,0.00189075,0.0002000572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2641806,0.00007372557,0.7344508,0.00002466417,0.0006356485,0.0005419597,0.000001058379,0.00007744774,0.00001406495],"genre_scores_gemma":[0.918416,0.000003124376,0.08089738,0.00001877466,0.0003181608,0.00003826565,2.700901e-7,0.00001239494,0.0002956457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7544883,"threshold_uncertainty_score":0.5411112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09313325424547292,"score_gpt":0.2902617251158839,"score_spread":0.197128470870411,"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."}}