{"id":"W2209723504","doi":"","title":"On the use of holonic agents in the design of information fusion systems","year":2014,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thales (Canada); Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Computer science; Context (archaeology); Sensor fusion; Representation (politics); Information system; Information fusion; Fusion; Interpretation (philosophy); Context model; Knowledge representation and reasoning; Data modeling; Intelligent decision support system; Multi-agent system; Systems engineering; Artificial intelligence; Software engineering; Engineering; Programming language","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":[0.002067504,0.0001605844,0.0002327937,0.0002698806,0.0001125854,0.0001803031,0.001280847,0.0001284705,0.00000269142],"category_scores_gemma":[0.000700904,0.00009280616,0.00008081498,0.0006281093,0.00006402516,0.000608733,0.0001936386,0.0002235014,0.00001202133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009337932,"about_ca_system_score_gemma":0.00008559418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002389912,"about_ca_topic_score_gemma":0.0001274352,"domain_scores_codex":[0.9980311,0.0006561365,0.0004587098,0.0001629867,0.0003949088,0.0002961298],"domain_scores_gemma":[0.9975349,0.0009047478,0.000381841,0.001014577,0.0001143724,0.00004953187],"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":[0.00004957955,0.0002174029,0.004009861,0.00005574766,0.00001557495,0.000003272688,0.003173362,0.03800767,0.0007803612,0.9343532,0.005783186,0.01355076],"study_design_scores_gemma":[0.0002933392,0.0003007072,0.02845475,0.0001089962,0.000007539326,0.00001813256,0.00006254619,0.962827,0.001994249,0.003782738,0.00200738,0.000142605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07553704,0.000110502,0.922076,0.0008288815,0.0001153982,0.0007796069,0.000003435879,0.0000864792,0.0004626187],"genre_scores_gemma":[0.9881816,0.00005162898,0.01059034,0.0009449541,0.00001994792,0.0001559398,0.000002819414,0.000007552052,0.00004519385],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9305705,"threshold_uncertainty_score":0.3784526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03590871436453831,"score_gpt":0.2322286035571631,"score_spread":0.1963198891926248,"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."}}