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Record W2000889337 · doi:10.1002/mrm.22196

Quantitative sodium MRI of the mouse prostate

2010· article· en· W2000889337 on OpenAlexaff
Jamie Near, Robert Bartha

Bibliographic record

VenueMagnetic Resonance in Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsRobarts Clinical TrialsWestern University
Fundersnot available
KeywordsImaging phantomProstateSodiumChemistryNuclear magnetic resonanceNuclear medicineRepeatabilityMedicinePhysicsChromatographyInternal medicineCancer

Abstract

fetched live from OpenAlex

A method was developed for quantitative sodium MRI of the mouse prostate at 9.4 T. A small loop-gap radiofrequency coil was constructed and dual-tuned to both the proton and sodium frequencies. The location and boundary of the mouse prostate were localized using high-resolution T(2)-weighted proton images, and sodium images were acquired with 1mm isotropic resolution using a short echo time (0.6 ms) and a long pulse repetition time (300 ms) for sodium density weighting with minimal T(1) and T(2) contrast. Sodium concentration in the prostate was estimated by comparing pixel intensities within the prostate to the pixel intensities in a pair of reference vials with known sodium concentrations, and a radiofrequency field inhomogeneity correction was performed based on field maps of a homogeneous phantom. In a group of five healthy, 5-month-old BALB/c mice, the average sodium concentration within their prostates was measured to be 173 +/- 38 mM. Muscle tissue and bladder were also clearly visible in the sodium images, and their sodium concentrations were estimated to be 40 +/- 15 mM and 210 +/- 72 mM, respectively.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.328
Teacher spread0.311 · 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
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

Citations12
Published2010
Admission routes1
Has abstractyes

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