Validation of the poke-flow technique combined with simulations of fluid flow for determining viscosities in samples with small volumes and high viscosities
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Bibliographic record
Abstract
Abstract. Viscosity in particles consisting of secondary organic material (SOM) has recently become an area of research focus, since information on viscosity is needed to predict the environmental impacts of SOM particles. Recently Renbaum-Wolff et al. (2013a) developed a poke-flow technique that was combined with simulations of fluid flow to constrain the viscosities of SOM samples of 1–5 mg mass, roughly the maximum that may be collected from environmental chambers or flow tubes on a reasonable timescale. The current manuscript expands on the initial validation experiments carried out by Renbaum-Wolff et al. First, the poke-flow technique combined with simulations of fluid flow was used to determine the viscosity of sucrose–water particles over a relatively wide range of relative humidities (RHs). The lower and upper limits of viscosity at 59% RH were 1.0 × 101 and 1.6 × 104 Pa s, whilst at 37% RH the corresponding values were 7.2 × 104 and 4.7 × 106 Pa s, respectively. The results are in good agreement with recent measurements by Quintas et al. (2006) and Power et al. (2013). Second, the approach was used to determine the viscosity of two polybutene standards. The simulated lower and upper limits of viscosity for standard #1 was 2.0 × 102 and 1.2 × 104 Pa s, whilst for standard #2 the corresponding values were 3.1 × 102 and 2.4 × 104 Pa s. These values are in good agreement with values reported by the manufacturer. The results for both the sucrose–water particles and the polybutene standards show that the poke-flow technique combined with simulations of fluid flow is capable of providing both lower and upper limits of viscosity that are consistent with literature or measured values when the viscosity of the particles are in the range of ≈ 5 × 102 to ≈ 3 × 106 Pa s.
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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 | 0.001 | 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.
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