Characterization of Fibres and Fibre Collectives with Common Laser Diffractometers
Why this work is in the frame
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Bibliographic record
Abstract
The method described utilises the effect that in many commercially available laser diffractometers a laminary flow of the suspension medium in the measurement cell exists. However, data analysis carried out using commercially available laser diffractometers is normally based upon the assumption that there is a statistical orientation of the particles in the measurement volume. The resulting diffraction patterns are, therefore, assumed to be centrosymmetric and ring-shaped. As a consequence, the detectors commonly used only record parts of the diffraction patterns. Based upon these assumptions, it is accepted that grain size analysis of fibrous particles gives an equivalent diameter between length and diameter. First experiments carried out using a Malvern Mastersizer X showed that fibres align in the flow direction. Analysis of the entire diffraction pattern should, therefore, provide information about the length and diameter of the fibres.
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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 | 0.001 |
| 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