{"id":"W4411805355","doi":"10.36680/j.itcon.2025.044","title":"Process time estimation for workstations in modular construction production line","year":2025,"lang":"en","type":"article","venue":"Journal of Information Technology in Construction","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Workstation; Modular design; Production (economics); Process (computing); Production line; Estimation; Computer science; Line (geometry); Engineering; Manufacturing engineering; Industrial engineering; Systems engineering; Engineering drawing; Mechanical engineering; Operating system; Mathematics","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":[0.000436157,0.001012181,0.0004840733,0.0008195044,0.0003639341,0.0005894368,0.0005074624,0.0007130315,0.0014449],"category_scores_gemma":[0.001344189,0.0003444292,0.0005303416,0.0008358406,0.000225822,0.0005997624,0.0003554698,0.0007206512,0.0003444489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008513279,"about_ca_system_score_gemma":0.0006500405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01037709,"about_ca_topic_score_gemma":0.00885319,"domain_scores_codex":[0.9997665,0.0000343995,0.00001108054,0.00008695585,0.00007077853,0.00003025364],"domain_scores_gemma":[0.9994623,0.0002457766,0.0001093178,0.00004436956,0.0001051581,0.00003299071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002199908,0.000116352,0.01121549,0.00005880265,0.00001953332,0.000122099,0.00008336733,0.93077,0.01085147,0.0002984218,0.0003970413,0.04584739],"study_design_scores_gemma":[0.000003658153,0.00003877465,0.003201914,0.000002678903,0.000004488393,0.000009758452,0.00002028817,0.9924448,0.004000484,0.0001532117,0.0001135933,0.000006364029],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7857667,0.0001693372,0.2106545,0.00009011359,0.00002297983,0.00003853245,0.0003173452,0.001133282,0.001807275],"genre_scores_gemma":[0.9826328,0.00005839365,0.01626815,0.000006869802,0.000003047323,0.00002027974,0.0002674733,0.00003276999,0.0007102835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01037709,"threshold_uncertainty_score":0.0206334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002803335195913912,"score_gpt":0.2199780160392228,"score_spread":0.2171746808433088,"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."}}