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Record W2305163875 · doi:10.4137/mri.s23559

Fluorine-19 Mri Contrast Agents for Cell Tracking and Lung Imaging

2015· review· en· W2305163875 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMagnetic Resonance Insights · 2015
Typereview
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsRobarts Clinical TrialsWestern University
Fundersnot available
KeywordsContrast (vision)LungTracking (education)Magnetic resonance imagingMedicineRadiologyComputer scienceComputer visionPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Fluorine-19 ((19)F)-based contrast agents for magnetic resonance imaging stand to revolutionize imaging-based research and clinical trials in several fields of medical intervention. First, their use in characterizing in vivo cell behavior may help bring cellular therapy closer to clinical acceptance. Second, their use in lung imaging provides novel noninvasive interrogation of the ventilated airspaces without the need for complicated, hard-to-distribute hardware. This article reviews the current state of (19)F-based cell tracking and lung imaging using magnetic resonance imaging and describes the link between the methods across these fields and how they may mutually benefit from solutions to mutual problems encountered when imaging (19)F-containing compounds, as well as hardware and software advancements.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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 head0.045
GPT teacher head0.344
Teacher spread0.298 · 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