{"id":"W2149463069","doi":"10.1109/simsym.1994.283113","title":"The resolution of an open-loop resource allocation problem using a neural network approach","year":2002,"lang":"en","type":"article","venue":"","topic":"Military Defense Systems Analysis","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Asynchronous communication; Resource allocation; Artificial neural network; Scheduling (production processes); Constraint satisfaction; Context (archaeology); Artificial intelligence; Mathematical optimization; Greedy algorithm; Strengths and weaknesses; Resource management (computing); Distributed computing; Algorithm; Mathematics; Computer network","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":[0.0006705381,0.000600713,0.0005716033,0.0003378177,0.000509575,0.000963838,0.0009454632,0.00127894,0.003450263],"category_scores_gemma":[0.001752216,0.0003523768,0.0003583818,0.0004303622,0.0006457733,0.001249906,0.0009248979,0.001186122,0.0003421233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007590992,"about_ca_system_score_gemma":0.001145691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007130534,"about_ca_topic_score_gemma":0.006488254,"domain_scores_codex":[0.9997491,0.00007338607,0.00001293304,0.00005993527,0.00006305517,0.00004152102],"domain_scores_gemma":[0.9995395,0.0003116112,0.00004407061,0.00002317252,0.00006004982,0.00002157421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002974512,0.00002518729,0.0001339567,0.00003195629,0.00001408005,0.00005233855,0.0000272318,0.9470025,0.001401777,0.0102186,0.0006826579,0.04037997],"study_design_scores_gemma":[0.000003205396,0.000006299943,0.00001634217,0.000002608129,0.000001932321,0.000006803086,0.000003530317,0.9967134,0.0002488213,0.002735879,0.0002591928,0.000002033079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006162921,0.0001074953,0.9912878,0.0001324532,0.00002019643,0.00001935212,0.00001588374,0.0001741731,0.00207987],"genre_scores_gemma":[0.4277773,0.000309885,0.5643175,0.0001821816,0.00009165586,0.0002425196,0.0001003758,0.0001062685,0.006872397],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007130534,"threshold_uncertainty_score":0.01417804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03209665360038017,"score_gpt":0.2215743617637245,"score_spread":0.1894777081633443,"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."}}