MétaCan
Menu
Back to cohort
Record W1969428076 · doi:10.1002/nbm.685

Relaxation times and microstructures

2001· review· en· W1969428076 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 · 2001
Typereview
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversity of Alberta
FundersMedical Research CouncilMedical Research Council CanadaFondation pour la Recherche Médicale
KeywordsRelaxation (psychology)Biological systemSampling (signal processing)Focus (optics)MicrostructureNuclear magnetic resonancePrincipal component analysisSample (material)Component (thermodynamics)Computer scienceStatistical physicsChemistryComputational physicsMaterials sciencePhysicsArtificial intelligenceOpticsThermodynamicsChromatographyBiologyNeuroscienceComputer vision

Abstract

fetched live from OpenAlex

Abstract A discussion is presented of the evaluation of multiple relaxation components from water protons in biological tissue. The principal focus is to draw attention to the way in which limitations in the raw NMR data, such as signal‐to‐noise ratio, data sampling density and acquisition window width, affect the precision and resolution in the processed multiple component solution of the return to thermal equilibrium. The second issue discussed is the interpretation of these multiple components in terms of microstructural compartments of the biological sample and, thirdly, we outline some of the successes in determining regional and pathological variations in microstructure in the human body in‐vivo , using the technique of multiple relaxation components. Copyright © 2001 John Wiley & Sons, Ltd. Abbreviations used: CNS central nervous system CPMG Carr–Purcell–Meiboom–Gill sequence RBC red blood cells NMR nuclear magnetic resonance NNLS non‐negative least squares PNS peripheral nervous system SNR signal‐to‐noise ratio TE echo time.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.385
Teacher spread0.369 · 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