{"id":"W2014762089","doi":"10.1115/detc2009-86263","title":"Customer-Centric Product Modeling for Rapid Product Identification in One-of-a-Kind Production","year":2009,"lang":"en","type":"article","venue":"","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Identification (biology); Product (mathematics); Data mining; Production (economics); Fuzzy logic; Process (computing); New product development; Cluster analysis; Industrial engineering; Quality (philosophy); Scheme (mathematics); Machine learning; Artificial intelligence; Engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001171206,0.0001973584,0.0002581033,0.0008347692,0.0001338826,0.0001251529,0.0002193334,0.00004758354,0.00005396864],"category_scores_gemma":[0.000590873,0.0001967496,0.0000576516,0.001655897,0.00001990619,0.001942534,0.00003318152,0.00009386623,0.00006394549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006770996,"about_ca_system_score_gemma":0.00005586925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003348504,"about_ca_topic_score_gemma":0.00002385129,"domain_scores_codex":[0.9979856,0.00001198576,0.0006849804,0.0006696086,0.0003187832,0.0003290295],"domain_scores_gemma":[0.9987108,0.000007192942,0.0003414817,0.0003662329,0.0005651417,0.000009227637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001114551,0.00316756,0.02870346,0.002000666,0.0001120736,0.000001939957,0.0008311793,0.04144258,0.1309783,0.04530745,0.0223688,0.7239715],"study_design_scores_gemma":[0.00830885,0.0001210134,0.2008735,0.0008324721,0.0006775531,0.00001103311,0.00105811,0.3650475,0.305428,0.05976166,0.05345801,0.004422234],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9571911,0.0005339922,0.01305335,0.01223778,0.002101234,0.005156049,0.000001625531,0.0004284169,0.009296416],"genre_scores_gemma":[0.9956014,0.00004481051,0.001480802,0.0002014606,0.001613388,0.00007410597,0.0001322853,0.00002361832,0.0008281071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7195492,"threshold_uncertainty_score":0.8023217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03366742587689762,"score_gpt":0.236577956702112,"score_spread":0.2029105308252144,"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."}}