{"id":"W3207822365","doi":"10.32920/14655120.v1","title":"Plane wave ultrasound imaging using synthetic aperture image reconstruction techniques","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Image quality; Iterative reconstruction; Image plane; Synthetic aperture radar; Optics; Plane wave; Aperture (computer memory); Computer vision; Artificial intelligence; Computer science; Physics; Image (mathematics); Acoustics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005927602,0.0005443199,0.0003533658,0.0004448621,0.0001106924,0.0008682631,0.0003602837,0.0005848742,0.001474465],"category_scores_gemma":[0.001360536,0.0002967844,0.0005215108,0.0005197372,0.0003536449,0.0009399139,0.0004815054,0.0006750131,0.0009599567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002016184,"about_ca_system_score_gemma":0.0003244544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002771893,"about_ca_topic_score_gemma":0.0002516506,"domain_scores_codex":[0.9996402,0.00007653739,0.00002145577,0.00004935004,0.0001944389,0.00001794397],"domain_scores_gemma":[0.9994431,0.0001947268,0.00008234666,0.0001109966,0.0001530047,0.00001583733],"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":[0.0002418309,0.00009038456,0.00108237,0.0004608546,0.0001077126,0.0002541331,0.0002471807,0.1039566,0.5311956,0.05406534,0.001606168,0.3066917],"study_design_scores_gemma":[0.00001639075,0.0001240852,0.0004390562,0.0000189014,0.00001631463,0.0005178948,0.00003318586,0.8166873,0.1711347,0.00482498,0.00615894,0.00002825897],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01112026,0.0001077498,0.9873468,0.00004281847,0.00001312214,0.00002555448,0.00003434074,0.0002569586,0.001052371],"genre_scores_gemma":[0.1004521,0.0004669398,0.8964656,0.00002959318,0.00001837633,0.00005206713,0.0001844758,0.0001004724,0.002230305],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001474465,"threshold_uncertainty_score":0.004932582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012902925847508,"score_gpt":0.208825836814703,"score_spread":0.1986968075562279,"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."}}