{"id":"W2697367259","doi":"10.1109/ccece.2017.7946614","title":"Small footprint high gain and low noise figure preamplifier for 7T MRI scanner","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Preamplifier; Footprint; Electromagnetic coil; Electrical impedance; Electrical engineering; Noise (video); Acoustics; Physics; Electronic engineering; Engineering; Computer science; Amplifier; CMOS","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":[0.0006243861,0.0007313079,0.0005398798,0.0004237611,0.0002905548,0.0005694773,0.001543306,0.001183553,0.00487086],"category_scores_gemma":[0.0009214846,0.0005330256,0.0003422982,0.0002649897,0.0003912269,0.0009959518,0.0005931024,0.0007548645,0.00406903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003238524,"about_ca_system_score_gemma":0.0006593808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002088377,"about_ca_topic_score_gemma":0.0007978798,"domain_scores_codex":[0.9994461,0.0000703634,0.00002654478,0.00009308897,0.0003307607,0.00003310654],"domain_scores_gemma":[0.9992779,0.0001598478,0.0001232159,0.00006666535,0.0002996614,0.00007270046],"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":[0.0002018683,0.00004870398,0.0009509794,0.0004307174,0.000039113,0.0006702664,0.0001237842,0.0007768715,0.945688,0.002801183,0.002527158,0.04574141],"study_design_scores_gemma":[0.00006487562,0.001743486,0.003536775,0.00009275623,0.0001833738,0.007867785,0.000152855,0.01866001,0.8991041,0.001438237,0.0670704,0.00008542464],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06195686,0.001254073,0.9250735,0.001067551,0.00033738,0.0004673337,0.0002745438,0.001982229,0.007586574],"genre_scores_gemma":[0.2231944,0.0009961027,0.7604727,0.0007602815,0.0002077604,0.000462218,0.0004996737,0.0002912944,0.01311553],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00487086,"threshold_uncertainty_score":0.01629466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03639869235136834,"score_gpt":0.32386573752609,"score_spread":0.2874670451747217,"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."}}