{"id":"W4406230929","doi":"10.1016/j.ijmecsci.2025.109930","title":"Dynamics analysis and multi-objective optimization for a dry friction damper","year":2025,"lang":"en","type":"article","venue":"International Journal of Mechanical Sciences","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Central South University; University of Calgary","keywords":"Dry friction; Damper; Dynamics (music); Structural engineering; Friction coefficient; Engineering; Materials science; Control theory (sociology); Computer science; Composite material; Physics; Control (management); Acoustics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004895444,0.00004963721,0.0001243365,0.0002890755,0.00004710109,0.00006560724,0.0001784325,0.0000382348,0.00001829605],"category_scores_gemma":[0.0001466368,0.00003848064,0.0000755105,0.0003156989,0.00002464632,0.0001989919,0.00001568685,0.00005029489,3.185229e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000886995,"about_ca_system_score_gemma":0.0000247432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002152728,"about_ca_topic_score_gemma":0.00006329492,"domain_scores_codex":[0.9993731,0.00001890393,0.0002616928,0.00007052912,0.0002116154,0.00006411431],"domain_scores_gemma":[0.9995293,0.0001561335,0.00008022773,0.00002641298,0.0001781823,0.0000297157],"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":[0.00001794958,0.00003340507,0.002245631,0.00001428073,0.0007915265,0.000001498271,0.0001980187,0.9668201,0.0005311077,0.01052776,0.00004988968,0.01876881],"study_design_scores_gemma":[0.0002238509,0.0000311879,0.0006636528,0.00003364357,0.00006602141,0.000004438185,0.0002461164,0.997082,0.0002697988,0.001272399,0.00006905713,0.00003786401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02876867,0.0000736419,0.9694369,0.0003848346,0.000929602,0.0000527165,0.000006808648,0.00001139533,0.0003354668],"genre_scores_gemma":[0.9626712,0.00006610251,0.03711523,0.00003866674,0.00006135408,0.000003252778,0.000001650663,0.000002105953,0.0000404099],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9339026,"threshold_uncertainty_score":0.1569195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01182661481237176,"score_gpt":0.2845485418384543,"score_spread":0.2727219270260826,"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."}}