{"id":"W6986203588","doi":"","title":"Optimizing the partitioning of tandem AGV systems using genetic and memetic algorithms","year":2008,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Row; CMOS; Column (typography); Integrated circuit; Electronic circuit; Row and column spaces; Chip; Circuit design; Transistor","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006180722,0.0006934069,0.0007949217,0.0009577764,0.0005221011,0.0009302439,0.001325448,0.001069401,0.0024679],"category_scores_gemma":[0.001546352,0.0005248021,0.0004581056,0.0004717593,0.0005634473,0.0009049838,0.0008543187,0.0005335819,0.0004355411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001340362,"about_ca_system_score_gemma":0.001029921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004282351,"about_ca_topic_score_gemma":0.005176463,"domain_scores_codex":[0.9997897,0.00006086422,0.000008169118,0.00003775489,0.00004388491,0.00005961578],"domain_scores_gemma":[0.9996395,0.0001812846,0.00004433605,0.00003335516,0.00006572346,0.00003567323],"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":[0.00004943212,0.00006966887,0.0004607313,0.00002710781,0.00002723458,0.00003807126,0.00003768478,0.9614865,0.003881671,0.002694348,0.0004945669,0.03073307],"study_design_scores_gemma":[0.00001145943,0.00003694061,0.00006497969,0.000003170406,0.000005165508,0.000007445152,0.00002182974,0.996752,0.0009280698,0.001813853,0.000351827,0.00000330152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3754661,0.0005457681,0.6028143,0.0004578039,0.00007516085,0.0002414245,0.00008880496,0.001033322,0.0192774],"genre_scores_gemma":[0.8239522,0.0001248227,0.1707562,0.0001594316,0.00001930039,0.0002916572,0.0001007415,0.000111646,0.004484062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004282351,"threshold_uncertainty_score":0.009725034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01783875294197769,"score_gpt":0.1987283034765002,"score_spread":0.1808895505345225,"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."}}