MétaCan
Menu
← Back to cohort
Record W6999832564

Development of a MRI phantom to emulate the relaxation times of the neonatal brain at 3 Tesla

2007· article· en· W6999832564 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2007
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsImaging phantomMagnetic resonance imagingRelaxation (psychology)T2 relaxationWhite matterSpin–spin relaxation
DOInot available

Abstract

fetched live from OpenAlex

Prematurity greatly increases the risk of neurological impairment in newborn infants. Magnetic resonance imaging (MRI) provides powerful techniques for non-invasively investigating the impact of premature birth on early brain development. Experimental testing of MRI techniques on human nenonates is not ethically appropriate. Our previous work has shown that techniques used for brain imaging in adults are not optimal for neonates. Therefore, there is a crucial need for phantoms that can mimic MRI properties of the neonatal brain. Polyvinyl alcohol cryogel (PVA-C) has been investigated as a MRI phantom material for the adult brain. Our previous work showed that MRI relaxation times (T1 and T2) of 6-15% PVA-C were lower than those reported for neonatal white matter at 2.30 Tesla. The objective of this study was to investigate the relationship between PVA-C relation times and temperature to determine if sufficiently long relaxation times could be obtained by increasing temperature.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.308
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueNPARC→Same topicAdvanced MRI Techniques and Applications→French-language works237,207→