{"id":"W2015117772","doi":"10.1007/s13349-012-0031-2","title":"Output-only de-tuning assessment of tuned mass dampers","year":2012,"lang":"en","type":"article","venue":"Journal of Civil Structural Health Monitoring","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Parametric statistics; Control theory (sociology); Principal component analysis; Modal; Engineering; Set (abstract data type); Computer science; Mathematics; Statistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005055958,0.000439774,0.0004416986,0.0003257531,0.0002747254,0.0004798552,0.0005436264,0.0008288951,0.00183929],"category_scores_gemma":[0.001481146,0.0001757325,0.0002472237,0.000139547,0.0002175764,0.0004957389,0.0004324871,0.0003189347,0.0002916121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000239508,"about_ca_system_score_gemma":0.0001309841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000790233,"about_ca_topic_score_gemma":0.001123993,"domain_scores_codex":[0.9995075,0.00009314922,0.00002008343,0.00009606935,0.0002344444,0.00004858136],"domain_scores_gemma":[0.9990422,0.0004669379,0.0001000176,0.0001128256,0.0002472009,0.00003073645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003301976,0.0004248491,0.009063045,0.0005762827,0.0001294088,0.0002801644,0.0003706662,0.09868626,0.689351,0.0008081467,0.0004991239,0.196509],"study_design_scores_gemma":[0.00008917704,0.001596942,0.02909126,0.00004615017,0.0001136214,0.000307565,0.00009774092,0.7381611,0.2283245,0.0004254362,0.001704061,0.00004244905],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8242877,0.0003182842,0.1692767,0.00008983775,0.00004555058,0.00006141578,0.0001180961,0.0007097943,0.005092544],"genre_scores_gemma":[0.9930757,0.00002878217,0.005876564,0.00001620085,0.00000423487,0.000009135923,0.0000335089,0.0000266723,0.0009291359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00183929,"threshold_uncertainty_score":0.006152987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03358232047566488,"score_gpt":0.359797653037819,"score_spread":0.3262153325621541,"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."}}