{"id":"W2981793643","doi":"10.3390/app9214483","title":"ARPS: A Framework for Development, Simulation, Evaluation, and Deployment of Multi-Agent Systems","year":2019,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Software deployment; Computer science; Distributed computing; Scenario testing; Systems engineering; Risk analysis (engineering); Software engineering; Variety (cybernetics); Engineering; 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":[0.001920002,0.0001085723,0.0001750463,0.000115045,0.0002051607,0.0001352523,0.0003839522,0.00005466088,0.00000714257],"category_scores_gemma":[0.00006727737,0.00008840352,0.00002280649,0.0003222241,0.00004982029,0.0002334151,0.00008171237,0.00003238383,0.00001976265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004109737,"about_ca_system_score_gemma":0.0001429126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001401213,"about_ca_topic_score_gemma":0.000004529662,"domain_scores_codex":[0.9983612,0.00004330563,0.0003872409,0.0004348158,0.0005803332,0.0001930911],"domain_scores_gemma":[0.99893,0.0003207182,0.0002849376,0.0002409501,0.0001692297,0.00005414048],"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":[0.00001529763,0.0002233266,0.02521382,0.000399217,0.0000722704,1.54342e-7,0.01063913,0.3041165,0.009400123,0.6129193,0.000128928,0.0368719],"study_design_scores_gemma":[0.0005452295,0.00004404483,0.008761828,0.00006882915,0.000007115955,5.402631e-7,0.0002867465,0.9844517,0.002683513,0.001379322,0.001611803,0.0001593113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2281576,0.0002583908,0.7695459,0.00003897144,0.0004076082,0.001392989,0.000001059746,0.00003494919,0.0001625483],"genre_scores_gemma":[0.8861039,0.00000293496,0.1136265,0.00004149028,0.00002333575,0.0001541888,0.000001584636,0.000004178586,0.00004190679],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6803352,"threshold_uncertainty_score":0.3604991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09291840789326851,"score_gpt":0.3467847353145672,"score_spread":0.2538663274212987,"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."}}