{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000706022,0.0002317352,0.000306389,0.0008153882,0.0002395082,0.0003723258,0.0004028173,0.00003013376,0.00009963627],"category_scores_gemma":[0.00007715221,0.000193647,0.00007149293,0.001391968,0.00004843056,0.001905178,0.0002433284,0.0001222968,0.00001934664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001671892,"about_ca_system_score_gemma":0.00006260882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004787801,"about_ca_topic_score_gemma":0.00004977095,"domain_scores_codex":[0.9978951,0.00001807642,0.0006904585,0.0002947147,0.0008209147,0.0002807895],"domain_scores_gemma":[0.9983101,0.000007715741,0.0003037283,0.0003414716,0.000992076,0.00004488272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000215237,0.0004936113,0.00163017,0.0004317172,0.0003669921,0.00001712234,0.0003414113,0.9275979,0.00008025778,0.06078692,0.001537282,0.006501376],"study_design_scores_gemma":[0.02150688,0.002476272,0.2839287,0.007910987,0.004706368,0.00005502285,0.02497516,0.04070528,0.003883156,0.008037341,0.5973251,0.004489692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5590177,0.0006524781,0.3847581,0.01597917,0.001151834,0.002924827,0.000009097073,0.0001124253,0.03539428],"genre_scores_gemma":[0.9785129,0.0001756523,0.01879858,0.001336991,0.0006317194,0.00003807981,0.00001837181,0.0000423891,0.0004453342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8868926,"threshold_uncertainty_score":0.7896694,"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."}}