Characterization of T1 bias from lipids in MOLLI and SASHA pulse sequences
Bibliographic record
Abstract
BackgroundIncreased myocardial T 1 values are associated with fibrosis and edema, while decreased values in Fabry disease have been attributed to the short T 1 of infiltrative lipids [1,2].The relationship between lipid concentration (LC) and best-fit T 1 values is unknown.This study aims to determine the dependence of MOLLI and SASHA T 1 values on LC.MOLLI and SASHA[3] T 1 mapping sequences are based on the bSSFP acquisition.bSSFP signal yield as a function of off-resonance frequency is well characterized [4,5], with phase inversion in sequential "bSSFP bands" and a profile shift as a function of resonance frequency, resulting in constructive/destructive interference between water and fat [6,7].We hypothesized that lipids may decrease or increase T 1 values as a function of offresonance frequency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".