{"id":"W4402602643","doi":"10.1007/978-3-031-61499-6_2","title":"Construction Supply Chain Analysis on Forecasting the Demand for Small Equipment, Tools, and Consumables for Industrial Construction Projects","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Evaluation and Optimization Models","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"PCL Construction (Canada); University of Alberta","funders":"","keywords":"Consumables; Supply chain; Demand forecasting; Manufacturing engineering; Business; Operations management; Engineering; Computer science; Marketing","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":[0.0008961734,0.0007190313,0.0005354938,0.001180158,0.0003556325,0.000638129,0.0006259293,0.000723661,0.003695893],"category_scores_gemma":[0.001956662,0.0004111491,0.001024046,0.002229647,0.0003515237,0.000919364,0.0003838121,0.000739364,0.0002957306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322321,"about_ca_system_score_gemma":0.0009510448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05916895,"about_ca_topic_score_gemma":0.02928938,"domain_scores_codex":[0.9997413,0.00009306931,0.00001393661,0.0000446511,0.00006224767,0.00004484036],"domain_scores_gemma":[0.9988158,0.000964558,0.00003371541,0.00003870068,0.0001168998,0.00003034883],"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":[0.00008187385,0.00004870027,0.003110562,0.00004036143,0.00003144308,0.00005513177,0.00003431005,0.9619272,0.0008314878,0.002742807,0.0006887816,0.03040747],"study_design_scores_gemma":[0.00000218617,0.00001689614,0.0009032093,0.00000372487,0.000006091173,0.000003515769,0.00001037731,0.9969682,0.000184826,0.00175828,0.0001391433,0.000003520543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5687579,0.001430816,0.4072968,0.0006623752,0.0001245617,0.000210183,0.001801471,0.0004392818,0.01927673],"genre_scores_gemma":[0.9418952,0.000874311,0.04834177,0.00003817351,0.00004613048,0.00009225432,0.001367452,0.00006320605,0.007281567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05916895,"threshold_uncertainty_score":0.1176491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06132603582515857,"score_gpt":0.2393833139190139,"score_spread":0.1780572780938553,"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."}}