{"id":"W2110942504","doi":"10.1109/sensor.2009.5285510","title":"A MEMS sensor for mean shear stress measurements in high-speed turbulent flows with backside interconnects","year":2009,"lang":"en","type":"article","venue":"TRANSDUCERS 2009 - 2009 International Solid-State Sensors, Actuators and Microsystems Conference","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Capacitive sensing; Microelectromechanical systems; Materials science; Shear stress; Fabrication; Shear (geology); Capacitance; Turbulence; Stress (linguistics); Acoustics; Interconnection; Optoelectronics; Electrical engineering; Engineering; Composite material; Mechanics; Telecommunications; Physics","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":[0.0002947356,0.0006365721,0.0004925196,0.0004295255,0.0003522349,0.0004860355,0.0004317564,0.0005773938,0.0004561915],"category_scores_gemma":[0.0006860148,0.0003436976,0.0001951532,0.000237342,0.0002789605,0.0004585703,0.0003798876,0.0004359848,0.000248379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003229269,"about_ca_system_score_gemma":0.000401907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007141308,"about_ca_topic_score_gemma":0.001314453,"domain_scores_codex":[0.9995433,0.00004436499,0.00001887864,0.00008057839,0.0002735432,0.00003937653],"domain_scores_gemma":[0.9996287,0.00007398095,0.0000910061,0.00003505982,0.0001333479,0.00003791442],"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":[0.00006546585,0.00001204526,0.0007975027,0.00003577431,0.000004084224,0.0000470932,0.00003499916,0.0002742165,0.9921668,0.0001376242,0.000138582,0.00628581],"study_design_scores_gemma":[0.0000235274,0.0005543916,0.006643797,0.00001286437,0.00002261426,0.00043895,0.00003180944,0.01470775,0.9753642,0.00008715934,0.002075302,0.00003770957],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8668388,0.001405443,0.1268027,0.0002689156,0.0002584656,0.0001273055,0.0005031124,0.001146795,0.002648464],"genre_scores_gemma":[0.9352886,0.0003931152,0.06211977,0.00009090024,0.00007550994,0.00005404276,0.0001684303,0.00003177107,0.001777928],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0007141308,"threshold_uncertainty_score":0.002342999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01766152012553465,"score_gpt":0.2443836741575192,"score_spread":0.2267221540319846,"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."}}