{"id":"W2026504256","doi":"10.1080/00207540600699660","title":"Order quantities for style goods with two order opportunities and Bayesian updating of demand. Part I: no capacity constraints","year":2007,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Order (exchange); Factory (object-oriented programming); Finished good; Build to order; Operations research; Bayesian probability; Process (computing); Production (economics); Computer science; Economics; Microeconomics; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.003749271,0.001519732,0.001966632,0.00151232,0.000660874,0.003533911,0.002616962,0.002629131,0.006828991],"category_scores_gemma":[0.02969361,0.002432903,0.001671359,0.002710512,0.0023837,0.009038208,0.001502945,0.003250002,0.0007246904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003775743,"about_ca_system_score_gemma":0.001610079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01350125,"about_ca_topic_score_gemma":0.00985402,"domain_scores_codex":[0.996775,0.001083245,0.0001875182,0.0008367398,0.0008231922,0.0002943103],"domain_scores_gemma":[0.9773107,0.01725397,0.003292519,0.0007845096,0.0009898474,0.0003685406],"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":[0.0001430124,0.00008011104,0.001913706,0.0001677825,0.00005916359,0.0002270877,0.0001347633,0.836771,0.000693264,0.1376352,0.001825102,0.02034983],"study_design_scores_gemma":[0.00001910965,0.00003835164,0.0008979525,0.00001901405,0.00001703859,0.00006655944,0.00002771701,0.909963,0.0002499501,0.08745759,0.001205055,0.00003857617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06746448,0.001460947,0.9153621,0.001848104,0.0001307984,0.0001687629,0.0009614786,0.0001598856,0.01244346],"genre_scores_gemma":[0.8054421,0.001540624,0.1760406,0.0002821144,0.0002397448,0.0002390804,0.001105179,0.0002023649,0.01490828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01350125,"threshold_uncertainty_score":0.02739507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1479815675499393,"score_gpt":0.3646292880696174,"score_spread":0.2166477205196781,"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."}}