{"id":"W4402602513","doi":"10.1007/978-3-031-61499-6_8","title":"An Inventory Size Optimization of Manual Workstations in Steel Prefabrication","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Fredericton; University of New Brunswick","funders":"","keywords":"Prefabrication; Workstation; Computer science; Manufacturing engineering; Engineering drawing; Business; Operations management; Engineering; Operating system; Civil 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001120998,0.0003451302,0.0003326876,0.0006027987,0.00001247778,0.00004058257,0.0001680901,0.0004232943,0.0001236162],"category_scores_gemma":[0.00006138231,0.0004026507,0.00006104841,0.0001843978,0.00001554501,0.0001786876,0.00002395642,0.0005833922,0.000003849917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002418415,"about_ca_system_score_gemma":0.00002663141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001231782,"about_ca_topic_score_gemma":0.0003692373,"domain_scores_codex":[0.9987903,0.000005566223,0.0004926968,0.0003048605,0.0001936521,0.0002129747],"domain_scores_gemma":[0.9994322,0.0001330263,0.00007015704,0.0002757157,0.00003967493,0.00004921985],"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":[0.000004064717,0.000009633485,0.00002257614,0.0009365935,0.00002476775,0.000004944619,0.0004857445,0.9959272,0.00007401747,0.001047224,0.000006431502,0.001456759],"study_design_scores_gemma":[0.000139114,0.00001969309,0.0001180985,0.0009720142,0.00002945715,0.000001845172,0.000002434891,0.9951198,0.00056809,0.002115426,0.0005549237,0.0003590666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005124382,0.002700016,0.9784201,0.00003011917,0.0005786103,0.0004342618,0.0000275281,0.0004652279,0.01683172],"genre_scores_gemma":[0.9851555,0.0006570779,0.01242504,0.00001233084,0.000170684,0.00005565123,0.0002067508,0.0002276542,0.001089322],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.984643,"threshold_uncertainty_score":0.9998425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007111181245667265,"score_gpt":0.209811032485098,"score_spread":0.2026998512394307,"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."}}