Cassava flour slurry as a low‐cost alternative to commercially available gel for obstetrical ultrasound: a blinded non‐inferiority trial comparison of image quality
Bibliographic record
Abstract
OBJECTIVE: To evaluate the quality of ultrasound images obtained with cassava flour slurry (CFS) compared with conventional gel in order to determine objectively whether CFS could be a true low-cost alternative. DESIGN: Blinded non-inferiority trial. SETTING: Obstetrical ultrasound unit in an academic medical centre. POPULATION OR SAMPLE: Women with a singleton pregnancy, undergoing anatomy ultrasounds. METHODS: Thirty pregnant women had standard biometry measures obtained with CFS and conventional gel. Images were compared side-by-side in random order by two blinded sonologists and rated for image resolution, detail and total image quality using a 10-cm visual analogue scale. Ratings were compared using paired t-tests. Participant and sonographer experience was measured using five-point Likert scales. MAIN OUTCOME MEASURES: Image resolution, detail, and total image quality. Participant experience of gel regarding irritation, messiness, and ease of removal. RESULTS: We found no significant difference between perceived image quality obtained with CFS (mean = 6.2, SD = 1.2) and commercial gel (mean = 6.4, SD = 1.2) [t (28) = -1.1; P = 0.3]. Images were not rated significantly differently for either reviewer in any measure, any standardized image or any view of a specific anatomic structure. All five sonographers rated CFS as easy to obtain clear images and easy for patient and machine cleanup. Only one participant reported itching with CFS. CONCLUSIONS: CFS produces comparable image quality to commercial ultrasound gel. The dissemination of these results and the simple CFS recipe could significantly increase access to ultrasound for screening, monitoring and diagnostic purposes in resource-limited settings. FUNDING: This study was internally funded by our department. TWEETABLE ABSTRACT: Low-cost homemade cassava flour slurry creates images equal to commercial ultrasound gel, improving access.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".