MétaCan
Menu
Back to cohort

In vivo intravoxel incoherent motion measurements in the human placenta using echo-planar imaging at 0.5 TThis work was presented at the 5th Meeting of the ISMRMB in Vancouver, April 1997.

2000· article· en· W2615039562 on OpenAlexaboutno aff
Rachel J. Moore, Bashar Issa, Paweł Tokarczuk, Keith Duncan, Philip A. Boulby, Philip N. Baker, Richard Bowtell, B. S. Worthington, I. R. Johnson, Penny Gowland

Bibliographic record

VenueMagnetic Resonance in Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicMRI in cancer diagnosis
Canadian institutionsnot available
FundersMedical Research Council
KeywordsIntravoxel incoherent motionEcho-planar imagingEcho (communications protocol)PlanarMotion (physics)Nuclear magnetic resonanceComputer scienceMagnetic resonance imagingPhysicsMedicineComputer visionRadiologyDiffusion MRIComputer graphics (images)

Abstract

fetched live from OpenAlex

This paper presents the first in vivo measurements of intravoxel incoherent motion in the human placenta, obtained using the pulsed gradient spin echo (PGSE) sequence. The aims of this study were two-fold. The first was to provide an initial estimate of the values of the IVIM parameters in this organ, which are currently unknown. The second aim was then to use these results to optimize the sequence timings for future studies. The moving blood fraction (f), diffusion coefficient (D), and pseudo-diffusion coefficient (D*) were measured. The average value of f was 26 ± 6 % (mean ± SD), D was 1.7 ± 0.5 × 10−3 mm2/sec, and D* was 57 ± 41 × 10−3 mm2/sec. For the optimized values of b, the expected percentage uncertainty in the fitted values of f, D, and D* for the placenta were σf/f = 14.9%, σD/D = 14.3%, σD*/D* = 44.9%, for an image signal-to-noise of 20:1, and a total imaging time of 800 sec. Magn Reson Med 43:295–302, 2000. © 2000 Wiley-Liss, Inc.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.040
GPT teacher head0.307
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 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

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueMagnetic Resonance in MedicineSame topicMRI in cancer diagnosisFrench-language works237,207