{"id":"W2901339562","doi":"10.25071/10315/35270","title":"Improved Modal Contribution Factors As Response Tracking Mechanisms For Dynamic Systems During Design Optimization","year":2018,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bombardier (Canada); Carleton University","funders":"","keywords":"Computer science; Modal; Tracking (education); Control engineering; Control theory (sociology); Engineering; Control (management); Artificial intelligence; Materials science","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004536589,0.0003206641,0.0004480485,0.0008032043,0.000236427,0.0003569154,0.000624234,0.0003343289,0.00003293763],"category_scores_gemma":[0.01393023,0.000294452,0.000106185,0.0008188494,0.00004864749,0.0003219302,0.00005049223,0.0002471694,0.00001037235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136467,"about_ca_system_score_gemma":0.0004260603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001075362,"about_ca_topic_score_gemma":0.00122275,"domain_scores_codex":[0.9967893,0.0001528862,0.0008052947,0.0006823715,0.0005283179,0.00104187],"domain_scores_gemma":[0.9964736,0.001851545,0.0001460751,0.000447587,0.0004547295,0.0006264502],"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":[0.0003105226,0.00003021761,0.0000654035,0.00003751283,0.00002529913,0.00002659049,0.0001522422,0.9771149,0.008189755,0.01321947,0.000008172715,0.0008199339],"study_design_scores_gemma":[0.0006660441,0.0002980247,0.0003185229,0.0001061718,0.00001410461,0.00001895916,0.00006681235,0.991137,0.005381157,0.001557531,0.00008113725,0.0003544996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02801299,0.0001959147,0.9689837,0.0001690804,0.001150227,0.001262394,0.00005405542,0.0001689066,0.000002785574],"genre_scores_gemma":[0.9492156,0.000002817608,0.05031533,0.00001452969,0.00008901349,0.0002487649,0.00001100759,0.00005973723,0.00004323362],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9212026,"threshold_uncertainty_score":0.9999508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03394996725040571,"score_gpt":0.3018472131720031,"score_spread":0.2678972459215974,"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."}}