{"id":"W3215588322","doi":"10.1109/tuffc.2014.6805701","title":"S-sequence spatially-encoded synthetic aperture ultrasound imaging [Correspondence]","year":2014,"lang":"en","type":"letter","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Ultrasonic imaging; Synthetic aperture radar; Sequence (biology); Ultrasound; Computer science; Physics; Optics; Artificial intelligence; Acoustics; Chemistry","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":[0.0001801386,0.0002744361,0.0001752322,0.0002968634,0.00006980484,0.0002858783,0.0002952582,0.0004229153,0.00178087],"category_scores_gemma":[0.0005982164,0.0001435075,0.0001321726,0.0003078379,0.0002546558,0.000324555,0.0002109078,0.0001958526,0.0005721524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001183275,"about_ca_system_score_gemma":0.0001781585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002039626,"about_ca_topic_score_gemma":0.0004775866,"domain_scores_codex":[0.9998999,0.00002466504,0.000007021442,0.00001673322,0.00004377045,0.00000796202],"domain_scores_gemma":[0.9996681,0.00009756374,0.00006836251,0.0000531264,0.00009464313,0.00001820857],"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":[0.0002959768,0.00004862608,0.0006150493,0.0002538986,0.00002050199,0.0002050329,0.00005585917,0.00642213,0.8589554,0.004437438,0.001288244,0.1274018],"study_design_scores_gemma":[0.0000377655,0.0003576601,0.001374695,0.00003076962,0.00002359227,0.001534326,0.00003240409,0.1522254,0.8288663,0.001427611,0.01405616,0.00003337081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.2266755,0.0009892156,0.7550937,0.0003171731,0.0001309679,0.00008258897,0.000215011,0.001991412,0.01450432],"genre_scores_gemma":[0.5237131,0.0006431465,0.467003,0.000167456,0.00004859831,0.00004704868,0.000342757,0.0001136483,0.007921171],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.00178087,"threshold_uncertainty_score":0.005957603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210744277973502,"score_gpt":0.2359048618350493,"score_spread":0.2237974190553143,"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."}}