{"id":"W1969279919","doi":"10.1108/02602280910926841","title":"Simple and versatile micro‐cantilever sensors","year":2009,"lang":"en","type":"article","venue":"Sensor Review","topic":"Mechanical and Optical Resonators","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Department of National Defence","funders":"","keywords":"Cantilever; Frequency response; Natural frequency; Added mass; Position (finance); Materials science; Frequency domain; Acoustics; Biological system; Engineering; Structural engineering; Physics; Mathematics; Electrical engineering; Vibration; Mathematical analysis","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":[0.0008320494,0.0007362391,0.0006977857,0.0007565503,0.0003437672,0.0006703148,0.001404775,0.001286521,0.004367049],"category_scores_gemma":[0.001202291,0.0005781898,0.0004670089,0.0004316513,0.0003938918,0.001153401,0.001098437,0.0009166224,0.00178403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004232365,"about_ca_system_score_gemma":0.000280351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005614039,"about_ca_topic_score_gemma":0.001538457,"domain_scores_codex":[0.9984263,0.000101359,0.00006992788,0.0002695147,0.00104751,0.00008538533],"domain_scores_gemma":[0.9994593,0.0001600061,0.00005917845,0.0000771739,0.0002024655,0.00004186683],"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":[0.00008605214,0.00003256933,0.0005853136,0.000524914,0.00001949901,0.0001140521,0.00006873497,0.000869376,0.951462,0.001880983,0.001229354,0.04312712],"study_design_scores_gemma":[0.00005963551,0.0005862716,0.008500512,0.0001681706,0.00008012309,0.001512123,0.0001680852,0.02564334,0.8939334,0.002473496,0.06674735,0.0001275043],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2341453,0.02642922,0.6996084,0.001620141,0.001792034,0.001751805,0.002135824,0.003974766,0.02854262],"genre_scores_gemma":[0.4884046,0.005125278,0.490396,0.0007911155,0.0002740966,0.0008673372,0.0007123112,0.0001492324,0.01327998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004367049,"threshold_uncertainty_score":0.01460928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192803156051018,"score_gpt":0.2677923303288027,"score_spread":0.2558642987682925,"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."}}