Measurement of Water Diffusivities in Barley Components Using Diffusion Weighted Imaging and Validation with a Drying Model
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Bibliographic record
Abstract
Diffusion-weighted magnetic resonance imaging was used to determine water diffusion coefficients (D) in hull-less barley kernel components (endosperm and embryo) at 20.5±0.5°C. The D values in barley components were time-dependent and restricted in nature as indicated by the decrease in the apparent diffusion coefficient with increasing diffusion time (from 3 to 25 ms). A four-parameter Padé approximation model was used to estimate D and pore geometry (pore surface area–to-volume ratio, pore size, porosity, electrical conductivity and permeability of water) of the barley components after long diffusion time (t → ∞) using data obtained during a relatively short period of diffusion. The D of embryo and endosperm were 2.2±0.07 × 10−5 mm 2 Czuchajowska , Z. ; Klamczynski , A. ; Paszczynska , B. ; Baik , B.-K. Structure and functionality of barley starches . Cereal Chemistry 1998 , 75 ( 5 ), 747 – 754 .[Crossref] , [Google Scholar]/s and 1.0±0.10 × 10−5 mm 2 Czuchajowska , Z. ; Klamczynski , A. ; Paszczynska , B. ; Baik , B.-K. Structure and functionality of barley starches . Cereal Chemistry 1998 , 75 ( 5 ), 747 – 754 .[Crossref] , [Google Scholar]/s, respectively. These D values were used to simulate moisture and temperature patterns during the drying of a barley kernel using a two-dimensional simultaneous heat and moisture transfer model and compared with literature D values for validation purposes. Based on the comparison, the D values of barley components obtained from our study can be used to develop realistic models of water transport in barley during different postharvest processing operations (e.g., drying, kilning, steeping).
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it