MétaCan
Menu
Back to cohort
Record W2037605578 · doi:10.1002/mrm.20683

In vivo multiple‐mouse MRI at 7 Tesla

2005· article· en· W2037605578 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMagnetic Resonance in Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsScannerRadiofrequency coilMagnetic resonance imagingImaging phantomImage qualityElectromagnetic coilNuclear magnetic resonanceContrast (vision)IsotropyRadio frequencyDistortion (music)PhysicsNuclear medicineBiomedical engineeringOpticsComputer scienceMedicineImage (mathematics)RadiologyArtificial intelligence

Abstract

fetched live from OpenAlex

We developed a live high-field multiple-mouse magnetic resonance imaging method to increase the throughput of imaging studies involving large numbers of mice. Phantom experiments were performed in 7 shielded radiofrequency (RF) coils for concurrent imaging on a 7 Tesla MRI scanner outfitted with multiple transmit and receive channels to confirm uniform signal-to-noise ratio and minimal ghost artifacts across images from the different RF coils. Grid phantoms were used to measure image distortion in different positions in the coils. The brains of 7 live mice were imaged in 3D in the RF coil array, and a second array of 16 RF coils was used to 3D image the whole bodies of 16 fixed, contrast agent-perfused mice. The images of the 7 live mouse brains at 156 microm isotropic resolution and the 16 whole fixed mice at 100 microm isotropic resolution were of high quality and free of artifacts. We have thus shown that multiple-mouse MRI increases throughput for live and fixed mouse experiments by a factor equaling the number of RF coils in the scanner.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.314
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it