{"id":"W2023868887","doi":"10.1109/ultsym.2013.0153","title":"S-sequence encoded synthetic aperture B-scan ultrasound imaging","year":2013,"lang":"en","type":"article","venue":"","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Hadamard transform; Computer science; Synthetic aperture radar; Aperture (computer memory); Noise (video); Encoding (memory); Coded aperture; SIGNAL (programming language); Algorithm; Computer vision; Acoustics; Artificial intelligence; Image (mathematics); Physics; Telecommunications; Detector","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005404999,0.0001201228,0.0000879932,0.00003610577,0.00004756014,0.0001003472,0.0001135081,0.00003534236,0.001161104],"category_scores_gemma":[0.00008285742,0.0001018104,0.00003216476,0.00008893273,0.00002730732,0.0002003707,0.000008545875,0.0001146121,0.0004741349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005027163,"about_ca_system_score_gemma":0.000009324945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006889966,"about_ca_topic_score_gemma":0.000003873778,"domain_scores_codex":[0.9993846,0.000007187856,0.0001339002,0.0001349565,0.0001105674,0.0002288243],"domain_scores_gemma":[0.9995589,0.0001474759,0.0000131197,0.000169887,0.00003992216,0.00007073008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[2.663354e-7,0.000008114234,0.0003217208,0.00002526069,0.00001046953,0.000001690509,0.00009309882,0.002787771,0.9838076,0.0005401628,0.002697348,0.009706485],"study_design_scores_gemma":[0.0001961385,0.00001187751,0.001630859,0.00005497331,0.0000199868,0.00008626178,0.0003094936,0.935787,0.05363432,0.004158177,0.003607171,0.0005037579],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.507625,0.0007664567,0.354197,0.001118607,0.0007909529,0.000712285,0.00002928224,0.00150041,0.13326],"genre_scores_gemma":[0.9950263,0.00004901657,0.004210712,0.0002015079,0.00004848535,0.00002630696,0.00001220777,0.00002577229,0.0003997152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9329992,"threshold_uncertainty_score":0.999752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005811335646478072,"score_gpt":0.183972969985357,"score_spread":0.1781616343388789,"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."}}