Investigation of the mechanical properties of lignin nanofibrous structures using statistical modeling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The growing use of nanomaterials, environmental concerns and related industrial applications have provided unique opportunities for the development of nanofibers from natural biopolymers such as lignin. The main purpose of this study was to develop a direct relationship between lignin single nanofiber, the aligned nanofiber mat and the twisted nanofiber yarn’s strength using the weakest link theory of strength and the statistical model proposed for parallel fiber bundles. Twisted yarn strength was obtained via in situ mechanical properties of yarn constituent nanofibers affected by the Weibull distribution parameters, fiber fragmentation phenomenon, and obliquity. The results showed that the estimated strength of the single nanofiber and the aligned nanofiber mat was in a good agreement with the experimental data. As it might be expected, the yarn’s estimated strength was found to be highly influenced by the fiber fragmentation phenomenon.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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