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Record W1553722725 · doi:10.1002/nbm.1743

Spectral–spatial excitation for rapid imaging of DNP compounds

2011· article· en· W1553722725 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNMR in Biomedicine · 2011
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsHealth Sciences CentreGeneral Electric (Canada)University of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsCellular metabolismNuclear magnetic resonanceSpectral imagingHyperpolarization (physics)Cancer imagingPreclinical imagingChemistryIn vivoPhysicsOpticsNuclear magnetic resonance spectroscopyMedicineBiologyMetabolismBiochemistryCancer

Abstract

fetched live from OpenAlex

Dynamic nuclear polarization and dissolution offer the exciting possibility of imaging biochemical reactions in vivo, including some of the key enzymatic reactions involved in cellular metabolism. The development of new pulse sequence strategies has been motivated by demanding applications, such as the imaging of hyperpolarized metabolite distributions in the heart. In this article, the key considerations surrounding the application of spectral-spatial imaging pulse sequences for hyperpolarized (13)C metabolic imaging in cardiac and cancer applications are explored. Spiral pulse sequences for multislice imaging of [1-(13)C]pyruvate in the heart were developed, as well as time-resolved, three-dimensional, echo-planar imaging sequences for the imaging of [1-(13)C]pyruvate-lactate exchange in cancer. The advantages and challenges associated with these sequences were determined by testing in pig and rat models.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.308
Teacher spread0.278 · 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