MétaCan
Menu
Back to cohort
Record W3021536489 · doi:10.1186/s12968-020-00613-3

T1 mapping performance and measurement repeatability: results from the multi-national T1 mapping standardization phantom program (T1MES)

2020· article· en· W3021536489 on OpenAlexaff
Gabriella Captur, Abhiyan Bhandari, Rüdiger Brühl, Bernd Ittermann, Kathryn E. Keenan, Yang Ye, Richard J. Eames, Giulia Benedetti, Camilla Torlasco, Lewis Ricketts, Redha Boubertakh, Nasri Fatih, John P. Greenwood, Leonie E. Paulis, Chris Lawton, Chiara Bucciarelli‐Ducci, Hildo J. Lamb, Richard P. Steeds, Steve Leung, Colin Berry, Sinitsyn Valentin, Andrew Flett, Charlotte de Lange, Francesco De Cobelli, Magalie Viallon, Pierre Croisille, David Higgins, Andreas Greiser, Wenjie Pang, Christian Hamilton‐Craig, W. Strugnell, Tom Dresselaers, Andrea Barison, Dana Dawson, Andrew J. Taylor, François‐Pierre Mongeon, Sven Plein, Daniel Messroghli, Mouaz H. Al‐Mallah, Stuart M. Grieve, Massimo Lombardi, Jihye Jang, Michael Salerno, Nish Chaturvedi, Peter Kellman, David A. Bluemke, Reza Nezafat, Peter Gatehouse, James Moon

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2020
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersEuropean Association of Cardiovascular ImagingSiemens HealthineersUniversity College LondonBritish Heart FoundationMedical Research CouncilBarts CharityEuropean Society of CardiologyNational Institute for Health and Care Research
KeywordsRepeatabilityImaging phantomQuality assuranceNuclear medicineMedicineStandardizationCoefficient of variationReproducibilityBiomedical engineeringMedical physicsMathematicsStatisticsComputer sciencePathology

Abstract

fetched live from OpenAlex

The T 1 Mapping and Extracellular volume (ECV) Standardization (T1MES) program explored T 1 mapping quality assurance using a purpose-developed phantom with Food and Drug Administration (FDA) and Conformit Europenne (CE) regulatory clearance. We report T 1 measurement repeatability across centers describing sequence, magnet, and vendor performance.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0000.000

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 head0.072
GPT teacher head0.284
Teacher spread0.212 · 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 designOther design
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

Citations40
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cardiovascular Magnetic ResonanceSame topicAdvanced MRI Techniques and ApplicationsFrench-language works237,207