{"id":"W1992553170","doi":"10.1243/09544054jem1387","title":"Adaptable design: Concepts, methods, and applications","year":2009,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Design technology; Modular design; Product design; Systems engineering; Personalization; Computer science; Manufacturing engineering; Product (mathematics); Quality (philosophy); Design review (U.S. government); Engineering; Risk analysis (engineering); Business; Operations management; Product testing; World Wide Web","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":[0.0007564411,0.0001426098,0.0002712255,0.000182106,0.00005671635,0.00003715457,0.0002816874,0.00008790807,0.00001004001],"category_scores_gemma":[0.0003610903,0.0001043338,0.00008480765,0.000341834,0.00003119323,0.0006604473,0.00004625775,0.0002159631,6.390003e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002670689,"about_ca_system_score_gemma":0.00002666076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001032978,"about_ca_topic_score_gemma":3.812786e-8,"domain_scores_codex":[0.9990577,0.000002560716,0.0004533539,0.0001094906,0.0002428251,0.0001340654],"domain_scores_gemma":[0.9990666,0.00002736557,0.0004774909,0.00006635602,0.0003404077,0.00002177564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001955477,0.0001861899,0.00006910256,0.000829748,0.0002146477,0.000001109093,0.0001501011,0.2266307,0.2191268,0.5242183,0.004687912,0.02368983],"study_design_scores_gemma":[0.002049646,0.0001440795,0.001519136,0.0009692669,0.0005218288,0.00007635386,0.000260054,0.04389324,0.7296216,0.0193226,0.2009332,0.0006889228],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03200834,0.001050423,0.9625235,0.001864016,0.0009997693,0.000676111,0.000002008679,0.00008775338,0.0007881472],"genre_scores_gemma":[0.9570863,0.00006535083,0.04222189,0.0001146422,0.0004693336,0.000004398483,0.000001000916,0.00001042983,0.00002666698],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.925078,"threshold_uncertainty_score":0.4254609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01335750718545107,"score_gpt":0.2352807287514984,"score_spread":0.2219232215660473,"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."}}