{"id":"W1966153487","doi":"10.1016/j.jom.2004.10.008","title":"Managing build‐to‐order short life‐cycle products: benefits of pre‐season price incentives with standardization","year":2004,"lang":"en","type":"article","venue":"Journal of Operations Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Incentive; Commit; Microeconomics; Profit (economics); Economics; Order (exchange); Purchasing; Computer science; Finance; Operations management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002868428,0.0006148946,0.0007164587,0.0003783319,0.0004935998,0.001435061,0.001146017,0.0008449684,0.002618257],"category_scores_gemma":[0.01025787,0.0005193046,0.0006082179,0.0004779778,0.0008611867,0.002860554,0.00119787,0.001203477,0.0001999273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001121412,"about_ca_system_score_gemma":0.001611433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001749236,"about_ca_topic_score_gemma":0.001621121,"domain_scores_codex":[0.998737,0.0004947183,0.00005996168,0.0001434576,0.000305295,0.0002594873],"domain_scores_gemma":[0.9900798,0.00521743,0.002434405,0.0009832357,0.0006759703,0.0006091893],"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":[0.0005137431,0.0006467395,0.01076574,0.0001130607,0.00008579067,0.0002931458,0.0001443178,0.9068374,0.008416512,0.02767319,0.0006414211,0.04386888],"study_design_scores_gemma":[0.0001148761,0.0009502962,0.006632711,0.00002336396,0.00006829756,0.0001529823,0.0002007295,0.9371655,0.006071274,0.046751,0.001818555,0.00005042362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7837545,0.0003732673,0.2040353,0.0007215434,0.0000425803,0.0001895696,0.00006222694,0.0002116751,0.0106093],"genre_scores_gemma":[0.9949465,0.00005089492,0.00437899,0.00002671337,0.00001380753,0.00001565523,0.00001123107,0.000007902137,0.0005482836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002868428,"threshold_uncertainty_score":0.01516986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01134541843558551,"score_gpt":0.2308394570351333,"score_spread":0.2194940385995478,"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."}}