Comparison of new element designs for combined <scp>RF</scp>‐shim arrays at 7 T
Bibliographic record
Abstract
PURPOSE: To identify novel concepts for RF-shim loop architectures suitable for 7T made of two concentric conducting loops fulfilling RF and DC functions, respectively, and to determine their relative SNR performance. The goal is to minimize interference between the two systems while making efficient use of the space closest to the body. THEORY: We show by means of theoretical derivation of the frequency spectrum that the proposed two-loop structure exhibits an anti-resonant null and a resonant peak in the frequency domain. METHODS: The proposed structure is comprised of two concentric wire loops either arranged as nested loops or in the form of a coaxial cable, in which the two conductors carry the RF and shim signals, respectively. We use theory, simulation, and phantom measurements to obtain frequency spectra and SNR maps for the proposed structures. RESULTS: Retained SNR is found to be 75% in the coaxial loop and ranges from 57% to 67% in three different coaxial configurations. We have found both implementations to be a viable concept for the use in RF-shim devices if remaining SNR limitations can be overcome. CONCLUSIONS: We have investigated two new design modalities in 7T RF-shim coil design that separate the RF and shim conductors such that the previously proposed toroidal chokes are eliminated - thereby removing undesired additional loss, bulk, and design complexity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".