{"id":"W2000215570","doi":"10.1115/detc2013-13006","title":"Effective Reverse Engineering of Qualitative Design Knowledge: A Case Study of Aerospace Pylon Design","year":2013,"lang":"en","type":"article","venue":"Volume 4: 18th Design for Manufacturing and the Life Cycle Conference; 2013 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications","topic":"Technology Assessment and Management","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure; Concordia University","funders":"","keywords":"Capstone; Aerospace; Engineering management; Design knowledge; Computer science; Product design; Curriculum; Product lifecycle; Knowledge management; New product development; Engineering; Product (mathematics); Operations management; Business","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009567419,0.0002906108,0.0004678028,0.0001945891,0.0001653754,0.0001175947,0.0002349989,0.0001240593,0.00001487305],"category_scores_gemma":[0.0000303036,0.0002306729,0.00004919509,0.00007033088,0.0001543915,0.0001811533,0.00006304849,0.0002117466,0.000004440162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003779037,"about_ca_system_score_gemma":0.00003764229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004771068,"about_ca_topic_score_gemma":0.00001556663,"domain_scores_codex":[0.998549,0.0002441303,0.0004609167,0.000348069,0.0001560459,0.0002418792],"domain_scores_gemma":[0.9985189,0.0007057392,0.0002228606,0.0002704033,0.0001860126,0.00009609327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008630433,0.001128005,0.00005916052,0.002347613,0.005385945,0.00001568262,0.05215488,0.3709286,0.006486436,0.4938147,0.004174799,0.06264112],"study_design_scores_gemma":[0.002816254,0.0005501622,0.00005738979,0.0001904969,0.000207905,0.00003036713,0.03275779,0.9531593,0.002231178,0.007446618,0.0001911674,0.0003613165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1677796,0.0003563324,0.8272414,0.000130946,0.0001585866,0.004104989,0.0000199887,0.00009719924,0.000110942],"genre_scores_gemma":[0.9930725,0.0002735431,0.002777297,0.000005527329,0.00004524969,0.003566064,0.000004612108,0.00002614179,0.0002290634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8252929,"threshold_uncertainty_score":0.9406568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05778143921730841,"score_gpt":0.3120656877513391,"score_spread":0.2542842485340308,"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."}}