{"id":"W2272195081","doi":"10.48550/arxiv.1511.02182","title":"Optimizing Damper Connectors for Adjacent Buildings","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Damper; Retrofitting; Control theory (sociology); Heuristic; Mathematical optimization; Convergence (economics); Coupling (piping); Genetic algorithm; Optimization problem; Computer science; Mathematics; Structural engineering; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001701416,0.0002946926,0.0003627775,0.0001233715,0.0000792918,0.00004986225,0.0003858742,0.0003797137,0.0001077695],"category_scores_gemma":[0.00005788687,0.0003016346,0.0002184288,0.0001281012,0.00005595924,0.0001251145,0.0002563129,0.0003502305,0.00003725112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002185454,"about_ca_system_score_gemma":0.00005432527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000150646,"about_ca_topic_score_gemma":0.000009628168,"domain_scores_codex":[0.9989316,0.0000294225,0.0001811402,0.0004823403,0.00005041783,0.0003250649],"domain_scores_gemma":[0.9991636,0.00009874821,0.00005037559,0.0003425249,0.0001455196,0.0001992265],"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":[0.00003929829,0.0000176052,0.0001519569,0.00008437488,0.0001164008,0.00001683922,0.00008385425,0.9656121,0.0003828885,0.02995114,0.003413607,0.0001299737],"study_design_scores_gemma":[0.0009709114,0.0000530434,0.00004445579,0.00005904369,0.0001166171,0.000001110942,0.00008865834,0.9761623,0.0003800681,0.009519705,0.0120998,0.00050432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.268224,0.0004760108,0.7247143,0.00007277627,0.00141949,0.0005543806,0.00008092225,0.0007163741,0.003741731],"genre_scores_gemma":[0.99683,0.0001962481,0.001736594,0.00006412211,0.000197834,0.000004323444,0.00006488742,0.00003893733,0.0008670794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7286059,"threshold_uncertainty_score":0.9999436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07353934441508075,"score_gpt":0.1813709711217011,"score_spread":0.1078316267066203,"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."}}