{"id":"W4212827646","doi":"10.3389/fphy.2022.791145","title":"Ultrasound Contrast Imaging: Fundamentals and Emerging Technology","year":2022,"lang":"en","type":"article","venue":"Frontiers in Physics","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Heart and Stroke Foundation of Canada; Burroughs Wellcome Fund","keywords":"Ultrasound; Modality (human–computer interaction); Contrast-enhanced ultrasound; Scope (computer science); Diagnostic ultrasound; Medical imaging; Medical physics; Microbubbles; Medicine; Ultrasound imaging; Medical ultrasound; Contrast (vision); Radiology; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.00004414579,0.00009467871,0.0001273969,0.0000862934,0.0001369193,0.00001926818,0.0001170658,0.00001786134,0.00002456304],"category_scores_gemma":[0.000003285635,0.0001164464,0.00001991119,0.0003187707,0.00006631248,0.00006932617,0.00003292316,0.0002015815,0.000002280359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008741958,"about_ca_system_score_gemma":0.000007469331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004253822,"about_ca_topic_score_gemma":9.29384e-7,"domain_scores_codex":[0.9994805,0.000008935828,0.0001084939,0.0001369335,0.00007471013,0.0001904352],"domain_scores_gemma":[0.9997964,0.00001931728,0.00001633168,0.0001362955,0.000005830448,0.00002585753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001507804,0.0002662902,0.5250548,0.00007931696,0.0002002598,0.00001903977,0.003560057,0.02360555,0.1455732,0.01581194,0.05044711,0.2353674],"study_design_scores_gemma":[0.003703433,0.00008467626,0.01541683,0.00004491112,0.0001359833,0.0002735007,0.02933115,0.1050607,0.01720504,0.2656733,0.5609303,0.00214014],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8671707,0.008611303,0.1087836,0.0008052518,0.00165617,0.0006233582,0.0001604556,0.0009094945,0.01127968],"genre_scores_gemma":[0.997026,0.000110957,0.002523495,0.00006956056,0.00005530755,0.0001219517,0.00001836282,0.00002658839,0.00004780281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5104832,"threshold_uncertainty_score":0.4748545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004043827475642046,"score_gpt":0.1948394683182606,"score_spread":0.1907956408426185,"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."}}