{"id":"W2053099738","doi":"10.1109/tuffc.2009.1141","title":"Fabricating capacitive micromachined ultrasonic transducers with a novel silicon-nitride-Based wafer bonding process","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Capacitive micromachined ultrasonic transducers; Materials science; Wafer; Optoelectronics; Silicon nitride; Wafer bonding; Fabrication; Silicon on insulator; Capacitive sensing; Ultrasonic sensor; Microelectromechanical systems; Surface micromachining; Transducer; Silicon; Electrical engineering; Piezoelectricity; Composite material; Acoustics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001848585,0.0005252765,0.0005285058,0.0003067151,0.0003692686,0.0001236066,0.0001838763,0.0001913673,0.00002003957],"category_scores_gemma":[0.00003385304,0.0004847592,0.0001199957,0.0006949321,0.0000827812,0.0002705771,1.116249e-7,0.0005918522,0.000002237163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002019262,"about_ca_system_score_gemma":0.0001238815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004431999,"about_ca_topic_score_gemma":0.00004790954,"domain_scores_codex":[0.9979655,0.00004472048,0.0004651318,0.0005066161,0.0002785261,0.0007395801],"domain_scores_gemma":[0.9988796,0.0003926402,0.00009918356,0.0002641339,0.0001363727,0.0002280331],"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":[0.0001317303,0.0001046509,0.00001693855,0.00005050712,0.0001030756,0.000009505934,0.0003178103,0.3065447,0.684542,0.0003791108,0.00000149829,0.007798526],"study_design_scores_gemma":[0.008056396,0.001517598,0.0004815649,0.0002990721,0.0004566423,0.0001971961,0.0001648922,0.2822252,0.7038302,0.001029586,0.00004435748,0.00169724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3390926,0.0002040797,0.6590066,0.0001172183,0.000134751,0.0003572001,0.0001996231,0.0004436221,0.0004442717],"genre_scores_gemma":[0.9970105,0.00006348652,0.002380075,0.00028938,0.00004714457,0.00007967106,0.00001230008,0.00008784897,0.00002960135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6579179,"threshold_uncertainty_score":0.9997604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008353888983571587,"score_gpt":0.210979081808163,"score_spread":0.2026251928245914,"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."}}