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Record W1541366287 · doi:10.1002/jmri.24216

R2* as a surrogate measure of ferriscan iron quantification in thalassemia

2013· article· en· W1541366287 on OpenAlexaff
Wesley Chan, Zahra Tejani, Faisal Budhani, Christine Massey, Masoom A. Haider

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2013
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of TorontoMount Sinai HospitalSt. John’s Health Sciences CentreMemorial University of Newfoundland
FundersU.S. Food and Drug Administration
KeywordsMeasure (data warehouse)ThalassemiaBeta thalassemiaMedicineComputer scienceInternal medicineData mining

Abstract

fetched live from OpenAlex

PURPOSE: To determine whether R2* values are a consistent predictor of hepatic iron concentration (HIC) in thalassemia patients by demonstrating a correlation between R2* relaxation rates and FerriScan-determined HIC. MATERIALS AND METHODS: Eighty-eight patients with thalassemia major were retrospectively evaluated. All patients underwent FerriScan imaging and multiecho gradient echo imaging. The results from FerriScan analysis were fitted against R2* estimates using linear regression. RESULTS: There was a very strong linear correlation between R2* values and FerriScan-determined HIC (Spearman correlation of 0.976; 95% confidence interval [CI]: 0.963, 0.984). CONCLUSION: R2* values can predict HIC determined by FerriScan using a linear calibration curve. This technique may provide a potentially cost-saving alternative for hepatic iron determination and improve acceptance by referring physicians.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.250
Teacher spread0.242 · 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 designObservational
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

Citations25
Published2013
Admission routes1
Has abstractyes

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