{"id":"W2020817511","doi":"10.1155/2014/914347","title":"Development of a Hybrid Magnetic Resonance and Ultrasound Imaging System","year":2014,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Invention for Innovation; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; Medical Research Council; Department of Health and Social Care; Institute of Cancer Research; Cancer Research UK","keywords":"Imaging phantom; Transducer; Magnetic resonance imaging; Scanner; Ultrasound; Biomedical engineering; Materials science; Acoustics; Nuclear medicine; Medicine; Physics; Optics; Radiology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009917326,0.0003356053,0.000756235,0.000733084,0.0002614432,0.0007050675,0.001377114,0.001050244,0.004250741],"category_scores_gemma":[0.0008536917,0.0005307983,0.0003470406,0.0003309999,0.0002879677,0.0006697254,0.001137675,0.0006035704,0.002217546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000225021,"about_ca_system_score_gemma":0.0005105681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000334749,"about_ca_topic_score_gemma":0.0003987949,"domain_scores_codex":[0.9990647,0.00009861377,0.00006766536,0.0002447588,0.00046415,0.00006015212],"domain_scores_gemma":[0.9994376,0.0001353255,0.000061067,0.00007049889,0.0002141082,0.00008136783],"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":[0.0002614679,0.000122243,0.00120384,0.0003325661,0.00006968012,0.0004509469,0.0000979497,0.001393326,0.8677881,0.001866919,0.002019261,0.1243937],"study_design_scores_gemma":[0.0002510047,0.00520848,0.01349905,0.0001792587,0.0004462607,0.01321764,0.0001089514,0.07122231,0.772525,0.001138412,0.1218448,0.0003587526],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06596538,0.001481718,0.9205194,0.0003327713,0.0003627263,0.0005667227,0.0002712072,0.006489755,0.004010357],"genre_scores_gemma":[0.2018934,0.0008904937,0.7831359,0.0006015308,0.00018558,0.0009113487,0.0005541744,0.0001954391,0.01163216],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004250741,"threshold_uncertainty_score":0.01422012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03772863676669885,"score_gpt":0.3847972301072335,"score_spread":0.3470685933405346,"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."}}