{"id":"W3184553779","doi":"10.1016/j.aei.2021.101361","title":"Product redesign using functional backtrack with digital twin","year":2021,"lang":"en","type":"article","venue":"Advanced Engineering Informatics","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"National Natural Science Foundation of China","keywords":"Product (mathematics); Computer science; New product development; Product design; Process (computing); Function (biology); Field (mathematics); Space (punctuation); Product topology; Mathematics; Business","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004644437,0.0002433274,0.0001863355,0.00009809465,0.00004010494,0.0001698867,0.00009770739,0.0000683424,0.00003351333],"category_scores_gemma":[0.00003176074,0.0002497505,0.00004611627,0.0004557682,0.00002280331,0.002739853,0.0000178599,0.0002811065,0.00005901989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001246017,"about_ca_system_score_gemma":0.00005749304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.168796e-7,"about_ca_topic_score_gemma":1.531608e-7,"domain_scores_codex":[0.9988385,0.000001928181,0.0004506686,0.0000903921,0.0002823896,0.0003360916],"domain_scores_gemma":[0.9994162,0.00004214136,0.00003858607,0.0002730739,0.0001225363,0.000107482],"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":[0.00000351848,0.000009659781,0.00003938355,0.0002494944,0.00004776232,0.000006524292,0.0001779693,0.9881384,0.0007063048,0.0004436498,0.000116138,0.01006116],"study_design_scores_gemma":[0.0009498001,0.00003665799,0.0005274027,0.0003917245,0.00003067055,0.0005607945,0.0007550468,0.9033551,0.02984244,0.00004473827,0.06257679,0.0009288805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09833615,0.0001573489,0.8693434,0.00001221065,0.0005978442,0.0001814271,0.00004654399,0.0009463017,0.03037877],"genre_scores_gemma":[0.8888369,0.00002747879,0.1105315,0.00002673806,0.0001201056,0.00002204874,0.0001381254,0.0000869776,0.0002101752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7905007,"threshold_uncertainty_score":0.9999955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01396958067191897,"score_gpt":0.1899910661361435,"score_spread":0.1760214854642246,"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."}}