{"id":"W2888387017","doi":"10.1007/978-3-319-99540-3_19","title":"Compensation Techniques for Vibration Sensors with Application in Structural Health Monitoring","year":2018,"lang":"en","type":"book-chapter","venue":"Smart sensors, measurement and instrumentation","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Compensation (psychology); Structural health monitoring; Vibration; Acoustics; Computer science; Engineering; Structural engineering; Physics; Psychology; Social psychology","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":[0.0004298754,0.0004314634,0.000402503,0.0003573767,0.0001921848,0.00006595679,0.00008345857,0.0002618206,0.000008185428],"category_scores_gemma":[0.000009669651,0.0004357524,0.0000427341,0.00006850687,0.00006599683,0.0003183921,0.00001552167,0.0002565944,0.000002854331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001213035,"about_ca_system_score_gemma":0.0000596168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009905321,"about_ca_topic_score_gemma":0.0001804082,"domain_scores_codex":[0.9980329,0.00003090249,0.0006544015,0.0004277853,0.0005350562,0.0003189662],"domain_scores_gemma":[0.9990829,0.00002783632,0.0003090996,0.0002366949,0.0002503981,0.00009303259],"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":[0.0009729749,0.00003064955,0.01752263,0.006156499,0.0003987016,0.000003510506,0.005897406,0.0008994688,0.01489866,0.01156486,0.001677732,0.9399769],"study_design_scores_gemma":[0.0109167,0.008389743,0.2988477,0.01755672,0.0006661229,0.0001787445,0.002067233,0.08924843,0.4260449,0.06989139,0.06628275,0.009909595],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651574,0.0007502506,0.009254835,0.0005752566,0.002171235,0.01212246,0.000125678,0.002691082,0.007151815],"genre_scores_gemma":[0.9718037,0.0004378005,0.0258486,0.00003175409,0.000792842,0.0002933638,0.0003307225,0.0001462514,0.0003149226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9300673,"threshold_uncertainty_score":0.9998094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03796662436706311,"score_gpt":0.2802847914249084,"score_spread":0.2423181670578453,"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."}}