{"id":"W4411659899","doi":"10.1016/j.dib.2025.111837","title":"Order picking dataset from a warehouse of a footwear manufacturing company","year":2025,"lang":"en","type":"article","venue":"Data in Brief","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Order (exchange); Warehouse; Computer science; Manufacturing engineering; Business; Data science; Engineering; Marketing; Finance","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0000801626,0.0001117418,0.0001796317,0.0001058044,0.00002475291,0.00002253164,0.000425124,0.0000517855,0.00003049436],"category_scores_gemma":[0.0001222,0.0001228994,0.000008704204,0.0001147039,0.00002908817,0.000196992,0.0002535238,0.0001490271,0.000004833234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003184978,"about_ca_system_score_gemma":0.00001210921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006198938,"about_ca_topic_score_gemma":0.000255449,"domain_scores_codex":[0.999283,0.00001303841,0.0002396069,0.0002254599,0.00008167222,0.000157294],"domain_scores_gemma":[0.9989209,0.0001464113,0.00003120215,0.000869978,0.000009371694,0.00002217832],"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":[0.000008870072,0.00002295843,0.0004584206,0.00008522216,0.00003051439,0.000007009593,0.00006024141,0.9901728,0.00007068953,0.0001170011,0.005270428,0.003695817],"study_design_scores_gemma":[0.00223057,0.00002125228,0.02535057,0.0005876041,0.00008991754,0.000001747697,0.0001659798,0.7106145,0.04168942,0.00278903,0.2157397,0.0007197869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04420922,0.0003913388,0.9387168,0.00004744437,0.0004256881,0.0001988189,0.01520756,0.0002465732,0.000556581],"genre_scores_gemma":[0.9504238,0.00009355209,0.03221749,0.00006219116,0.00002866079,0.000004923397,0.01713449,0.00002023394,0.00001461331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9064993,"threshold_uncertainty_score":0.5011691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285658327735635,"score_gpt":0.2662290104307193,"score_spread":0.243372427153363,"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."}}