{"id":"W1992694907","doi":"10.1109/iccse.2014.6926443","title":"A systematic approach for functional decomposition of mechatronic system design using mechatronic design quotient (MDQ)","year":2014,"lang":"en","type":"article","venue":"","topic":"Design Education and Practice","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mechatronics; Conceptual design; Process (computing); Engineering design process; Computer science; Systems engineering; Computer-automated design; Design process; Decomposition; Design methods; Identification (biology); Control engineering; Artificial intelligence; Engineering; Systems design; Work in process; Human–computer interaction; Mechanical engineering; Programming language","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":[0.001959035,0.0002127266,0.0003814669,0.0001903185,0.0001065851,0.00005271928,0.0001430221,0.0001077585,0.00003251552],"category_scores_gemma":[0.00008282129,0.0001964055,0.0001253104,0.0001866796,0.0000131184,0.0002643858,0.0000108465,0.00009774415,0.00002114993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000417288,"about_ca_system_score_gemma":0.0001024165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008150391,"about_ca_topic_score_gemma":4.419352e-7,"domain_scores_codex":[0.9982324,0.0004265881,0.000565999,0.0002247839,0.000256271,0.0002939487],"domain_scores_gemma":[0.9984562,0.0008256398,0.0001843742,0.0003008614,0.0001442944,0.00008861395],"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":[0.00006386099,0.00008170925,0.000001514671,0.01366219,0.0002043734,9.478377e-8,0.0001452116,0.9294488,0.01286062,0.04293051,0.0004802461,0.0001208608],"study_design_scores_gemma":[0.0004558918,0.0001164438,0.00000436426,0.00047498,0.0002695826,0.00004845923,0.0006559849,0.9881762,0.009298461,0.0002696447,0.00002381228,0.0002061429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005781189,0.0003164873,0.9954395,0.000009557575,0.0005792475,0.0017291,0.000002401317,0.0002851474,0.001060486],"genre_scores_gemma":[0.7152228,0.000003005316,0.2842898,0.00001402458,0.00007683681,0.0002783194,0.00001291554,0.00004047351,0.00006178631],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7146447,"threshold_uncertainty_score":0.8009184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04767356513497293,"score_gpt":0.2571298963011771,"score_spread":0.2094563311662042,"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."}}