{"id":"W2034359211","doi":"10.1080/00207540601099274","title":"Identification of the optimal product configuration and parameters based on individual customer requirements on performance and costs in one-of-a-kind production","year":2008,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Customer satisfaction; Identification (biology); Product (mathematics); Production (economics); Quality (philosophy); Engineering; Tree (set theory); Manufacturing engineering; Operations research; Industrial engineering; Computer science; Marketing; Business; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002848677,0.00009850904,0.0001426748,0.001078644,0.0001440489,0.00006795848,0.0002560301,0.00003901961,0.00001274704],"category_scores_gemma":[0.001507599,0.00007914677,0.00002768112,0.000636331,0.00023899,0.001055075,0.00006271263,0.0002805719,0.000004733222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001193608,"about_ca_system_score_gemma":0.0001093237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001883926,"about_ca_topic_score_gemma":0.000005769651,"domain_scores_codex":[0.9974523,0.00008812102,0.0006087497,0.000265834,0.001454682,0.000130336],"domain_scores_gemma":[0.9974068,0.00003891749,0.0006865465,0.0001637669,0.001692899,0.00001102035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00614847,0.002483386,0.647122,0.0005555794,0.0003436305,0.00001122416,0.002098868,0.04832773,0.1756555,0.003663142,0.007352822,0.1062377],"study_design_scores_gemma":[0.001168294,0.0001232712,0.7279353,0.0005984561,0.00002735392,0.00002320708,0.0002522976,0.002689333,0.2661452,0.000175721,0.0007027158,0.0001588562],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931313,0.00002044931,0.00003732742,0.004900977,0.001198789,0.00043423,0.000001204611,0.000004909023,0.0002707978],"genre_scores_gemma":[0.9990149,0.00008409286,0.0001128807,0.00005481403,0.0005608068,0.0000117889,0.000009292692,0.000009947371,0.0001414746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1060789,"threshold_uncertainty_score":0.3227512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1051983837186606,"score_gpt":0.3290606180300556,"score_spread":0.223862234311395,"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."}}