{"id":"W1989204558","doi":"10.1080/09537280500112181","title":"Coordinating product and process variety for mass customized order fulfilment","year":2005,"lang":"en","type":"article","venue":"Production Planning & Control","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mass customization; Variety (cybernetics); Order fulfillment; Product (mathematics); Engineering; Product design; Manufacturing engineering; Engineering management; Product management; Systems engineering; New product development; Computer science; Personalization; Business; Supply chain; World Wide Web; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001121544,0.0002627019,0.0003062337,0.0002345358,0.0005114715,0.0003063642,0.0001381309,0.00005992948,0.00004484174],"category_scores_gemma":[0.001114873,0.0002457469,0.00004223545,0.0004667575,0.00004542878,0.001618759,0.00003240956,0.0001418837,0.00003371822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005329352,"about_ca_system_score_gemma":0.00005143482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007521084,"about_ca_topic_score_gemma":0.000002079419,"domain_scores_codex":[0.9982255,0.00001534826,0.0004109683,0.0006962645,0.0002632443,0.0003887405],"domain_scores_gemma":[0.998708,0.00003536327,0.0003532894,0.0002056473,0.0006780578,0.00001963205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.007823802,0.001119371,0.2687412,0.004166849,0.001168379,0.000009165156,0.003677385,0.1073635,0.0623708,0.01594814,0.1490401,0.3785713],"study_design_scores_gemma":[0.02441699,0.00008068998,0.01944274,0.0004541714,0.0009715795,0.00003844964,0.001527173,0.2161007,0.01108476,0.006066898,0.7169743,0.002841594],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6646441,0.002989909,0.2152988,0.08700262,0.006468192,0.01193536,0.00001650112,0.002544655,0.009099841],"genre_scores_gemma":[0.9865865,0.000005409349,0.005706097,0.00102975,0.004924667,0.0004220868,0.00007493905,0.00004511771,0.001205494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5679342,"threshold_uncertainty_score":0.9999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132694481636247,"score_gpt":0.2364265585581992,"score_spread":0.2250996137418368,"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."}}