Fast spin‐echo for multiple mouse magnetic resonance phenotyping
Bibliographic record
Abstract
Abstract High‐resolution magnetic resonance imaging is emerging as a powerful tool for phenotyping mice in biologic studies of genetic expression, development, and disease progression. In several applications, notably random mutagenesis trials, large cohorts of mice must be examined for abnormalities that may occur in any part of the body. In the aim of establishing a protocol for imaging multiple mice simultaneously in a standardized high‐throughput fashion, this study investigates variations of a three‐dimensional fast spin‐echo sequence that implements driven equilibrium, modified refocusing, and partial excitation pulses. Sequence variations are compared by simulated and experimental measurements in phantoms and mice. Results indicate that when using a short repetition time (TR ≤ T1) a sequence employing a partial excitation tip angle provides both improved signal and good T2 contrast compared with standard fast spin‐echo imaging. This sequence is used to simultaneously acquire four live mouse head images at 100 μm isotropic resolution with a scan time under 3 h at 7 T. Magn Reson Med, 2005. © 2005 Wiley‐Liss, Inc.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".