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Record W2045621959 · doi:10.1097/rli.0b013e3180ca70e4

Development of a Composite Material Phantom Mimicking the Magnetic Resonance Parameters of the Neonatal Brain at 3.0 Tesla

2007· article· en· W2045621959 on OpenAlexaff
Timothy N. Orr, Inna Paliy, Jeff D. Winter, Gordon Campbell, Robert T. Thompson, Neil Gelman

Bibliographic record

VenueInvestigative Radiology · 2007
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsWestern UniversityLawson Health Research Institute
Fundersnot available
KeywordsImaging phantomMagnetic resonance imagingNuclear magnetic resonanceComposite numberMaterials scienceBiomedical engineeringNuclear medicineMedicineRadiologyPhysicsComposite material

Abstract

fetched live from OpenAlex

OBJECTIVE: Development of a composite material phantom, comprised of polyvinyl alcohol cryogel (PVA-C) and an agarose additive, to effectively mimic the magnetic resonance relaxation times (T1 and T2) of neonatal white matter (WM) and gray matter (GM) at 3.0 T. MATERIALS AND METHODS: Samples of PVA-C with and without agarose were prepared with 1 cycle of freezing/thawing. Measurements of T1 and T2, at 3.0 T, were performed on the samples at temperatures ranging from 20 degrees C to 40 degrees C. RESULTS: A sample temperature of 40 degrees C was required to achieve a T1 value sufficiently long to represent neonatal WM. At this temperature, neonatal WM relaxation times required 3% PVA-C with 0.3% agarose, whereas gray matter relaxation times required 8% PVA-C with 1.4% agarose. CONCLUSIONS: By adjusting the sample temperature, polyvinyl alcohol concentration, and agarose concentration, the relaxation times of neonatal brain tissues can be obtained using this composite material.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.540

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 studies0.0000.001
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 head0.027
GPT teacher head0.295
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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations8
Published2007
Admission routes1
Has abstractyes

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