{"id":"W1997509185","doi":"10.1109/tuffc.2009.1309","title":"The numerical analysis of general SAW and leaky wave devices using approximate Green's function representations","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Acoustic Wave Resonator Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"COM DEV International","funders":"University of Oxford","keywords":"Surface acoustic wave; Boundary element method; Lithium tantalate; Function (biology); Resonator; Green's function; Computer science; Finite element method; Filter (signal processing); Computational complexity theory; Acoustics; Algorithm; Electronic engineering; Lithium niobate; Optics; Physics; Engineering","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":[0.0005073678,0.0003141784,0.0004430271,0.0002738117,0.0002391974,0.0006095747,0.000506444,0.0006511934,0.001380012],"category_scores_gemma":[0.0008572213,0.00021604,0.0003832536,0.0003156541,0.000670217,0.0007529376,0.0003355143,0.0004036014,0.0002570863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003322985,"about_ca_system_score_gemma":0.0003857312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004976566,"about_ca_topic_score_gemma":0.0005424026,"domain_scores_codex":[0.9998672,0.00003215985,0.000006666126,0.0000135677,0.00006583417,0.00001461312],"domain_scores_gemma":[0.9997835,0.00014197,0.00001605839,0.00003127358,0.0000204636,0.000006709971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003815761,0.00002668677,0.0004683668,0.0002062171,0.00002272003,0.0001280473,0.0001082449,0.8047289,0.02685349,0.134521,0.0005553433,0.03234285],"study_design_scores_gemma":[0.000004863351,0.000009192616,0.00005440981,0.000003935059,0.000001762579,0.00002772329,0.000008126843,0.990415,0.001684953,0.007130065,0.0006564187,0.000003477669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03404716,0.0002178029,0.9608645,0.00008864062,0.00002202668,0.00002827313,0.00003564409,0.0001192992,0.004576534],"genre_scores_gemma":[0.4062817,0.0007448133,0.5854251,0.00006040372,0.00002548567,0.0002618717,0.00009751655,0.00007247166,0.007030612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001380012,"threshold_uncertainty_score":0.004616678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01271365294230659,"score_gpt":0.2286061023986174,"score_spread":0.2158924494563108,"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."}}