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Record W1964318960 · doi:10.1089/ars.2007.1625

Measuring Oxygenation <i>In Vivo</i> with MRS/MRI—From Gas Exchange to the Cell

2007· review· en· W1964318960 on OpenAlexafffund
Jeff F. Dunn

Bibliographic record

VenueAntioxidants and Redox Signaling · 2007
Typereview
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Calgary
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsOxygenationIn vivoChemistryMedicineBiologyAnesthesia

Abstract

fetched live from OpenAlex

Oxygen plays a major role as a substrate in metabolic processes in numerous signaling pathways, in redox metabolism, and in free radical metabolism. To study the role of oxygen in normal and pathophysiological states, methods that can be used noninvasively are required. This review examines the potential of nuclear magnetic resonance techniques to study tissue oxygenation. It is written from a systems perspective, looking at detection methods with respect to the path that oxygen takes in the mammalian system-from the lungs, through the vascular system, into the interstitial space, and finally into the cell. Methods discussed range from those that are quantifiable, such as the assessment of spin lattice relaxation time in fluorocarbon solutions, to those that are more correlative, such as assessment of lactate and high energy phosphates. Since the methods vary in their site of application, sensitivity, and specificity to the quantification of oxygen, this review provides examples of how each method has been applied. This may facilitate the reader's understanding of how to optimally apply different methods to study specific biomedical problems.

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.

How this classification was reachedexpand

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.061
GPT teacher head0.328
Teacher spread0.267 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2007
Admission routes2
Has abstractyes

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