Anthropomorphic MR Phantom of the Human Placenta for Sequence Optimization
Bibliographic record
Abstract
Fetal magnetic resonance imaging (MRI) is the gold standard for accurately diagnosing placental abnormalities suspected on ultrasound. Development of new MRI sequences optimized for fetal-placental imaging, however, is dependent on extensive testing. Using human volunteers is challenging due to the long scan times and high cost of participant recruitment. The ideal alternative is to use an anthropomorphic phantom of the human placenta that simulates placental anatomy and tissue properties in the womb. The aim of this project was to create an MR-phantom of an average third-trimester human placenta having: accurate gross anatomical structure and dimensions, and tissue properties corresponding to MRI, and dielectric properties. A MnCl /2garose doped carrageenan-hydrogel material mimicking the placentas relaxation time was developed to fill a 3D-printed phantom mould simulating the anatomical shape of the placenta. This novel placental phantom will offer the ability to rapidly develop, and test new imaging sequences designed for placental imaging.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".