{"id":"W2081245261","doi":"10.1109/tsmcc.2012.2213809","title":"Agent-Based Decision Support and Simulation for Wood Products Manufacturing","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Mill; Decision support system; Doors; Steel mill; Computer science; Production (economics); Manufacturing engineering; Negotiation; Industrial engineering; Ontology; Engineering; Artificial intelligence; Mechanical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001247329,0.0008675168,0.001160908,0.0004719444,0.0008314691,0.001761239,0.001371229,0.001465996,0.002800368],"category_scores_gemma":[0.00341207,0.0004727325,0.0007326248,0.0005809147,0.0007890174,0.0009429739,0.00113644,0.001474457,0.0003263427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001380587,"about_ca_system_score_gemma":0.001606783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01320159,"about_ca_topic_score_gemma":0.008864871,"domain_scores_codex":[0.9991459,0.0005144447,0.00005851032,0.00006723907,0.0001641402,0.00004977193],"domain_scores_gemma":[0.9974723,0.001975475,0.0001277915,0.00009573641,0.0002130401,0.0001154896],"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":[0.00006025103,0.00003591069,0.0001903066,0.000037291,0.00002268473,0.00004757956,0.00004752555,0.9861547,0.0002600871,0.006755127,0.0003012486,0.006087136],"study_design_scores_gemma":[0.00001319397,0.000008285422,0.00002006601,0.000003476528,0.000003227607,0.000003037062,0.000004950599,0.9969268,0.00009601725,0.002412903,0.0005050991,0.000002862472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05545637,0.000994329,0.9315389,0.0008234843,0.0001607947,0.0002677761,0.0002023707,0.001062085,0.009493928],"genre_scores_gemma":[0.7530636,0.0009717954,0.2415957,0.0001059871,0.00005944305,0.0005606659,0.0002575599,0.00006839113,0.003316794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01320159,"threshold_uncertainty_score":0.02624953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02743189120974773,"score_gpt":0.2661880533256117,"score_spread":0.238756162115864,"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."}}