{"id":"W1486569865","doi":"10.4271/2009-01-2152","title":"A Method for Torsional Damper Tuning Based On Baseline Frequency Response Functions","year":2009,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Chrysler (Canada)","funders":"","keywords":"Baseline (sea); Damper; Frequency response; Control theory (sociology); Computer science; Structural engineering; Engineering; Geology; Electrical engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007564581,0.001017574,0.0008264343,0.001148026,0.0004897892,0.0006850388,0.001669473,0.0007580352,0.01305262],"category_scores_gemma":[0.001627851,0.0005676256,0.0006305971,0.0007187106,0.0004144903,0.001019766,0.0007240305,0.001275048,0.005301525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004620181,"about_ca_system_score_gemma":0.0006120985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001088816,"about_ca_topic_score_gemma":0.001560501,"domain_scores_codex":[0.999119,0.0001076066,0.00004122426,0.0002025232,0.0004902925,0.00003944165],"domain_scores_gemma":[0.9994031,0.0002094436,0.00004744866,0.0001269351,0.0001922621,0.0000208227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000143555,0.00007516546,0.0003816675,0.0002578819,0.00003967599,0.0001136768,0.0001288135,0.01797822,0.1280397,0.01798235,0.005117992,0.8297414],"study_design_scores_gemma":[0.0001273891,0.000366613,0.002182861,0.0001013352,0.00009353692,0.001598568,0.00007099097,0.7481135,0.1419755,0.01543497,0.08971676,0.0002179435],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005995985,0.00004728481,0.9977078,0.00001042307,0.00002364411,0.00002694508,0.00001868575,0.0009176604,0.0006479617],"genre_scores_gemma":[0.02672604,0.0001452685,0.9678228,0.00002969624,0.00003446668,0.0001430324,0.0001061683,0.0003984416,0.004594043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01305262,"threshold_uncertainty_score":0.04366535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02014063216332855,"score_gpt":0.3085299467768117,"score_spread":0.2883893146134832,"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."}}