Bibliographic record
Abstract
The structural properties, the static and relaxation dielectric coefficients $[{\ensuremath{\epsilon}}_{j}$ and ${\ensuremath{\epsilon}}_{j}(\ensuremath{\omega})$ $(j=\ensuremath{\Vert},\ensuremath{\perp})],$ the rotational diffusion constants ${D}_{\ensuremath{\perp}}$ and ${D}_{\ensuremath{\Vert}},$ the orientational correlation times ${\ensuremath{\tau}}_{i0}^{1}$ $(i=0,1),$ and the bulk elastic constants ${K}_{i}$ $(i=1,2,3)$ are investigated for polar liquid crystals, such as $4\ensuremath{-}n\ensuremath{-}\mathrm{pentyl}\ensuremath{-}{4}^{\ensuremath{'}}\ensuremath{-}\mathrm{cyanobiphenyl}$ (5CB). ${\ensuremath{\epsilon}}_{j}$ are calculated by a combination of the existing molecular theory and statistical-mechanical approach (SMA) that takes into account translational and orientational correlations as well as their coupling, whereas ${\ensuremath{\epsilon}}_{j}(\ensuremath{\omega})$ are calculated by combining SMA and nuclear magnetic resonance relaxation theory, both based on a rotational diffusion model in which the reorientation of an individual molecule is assumed as stochastic Brownian motion in a potential of mean torque. Reasonable agreement between the calculated and experimental values of ${\ensuremath{\epsilon}}_{j}$ and ${\ensuremath{\epsilon}}_{j}(\ensuremath{\omega})$ for 5CB is obtained. The bulk Frank elastic constants ${K}_{i}$ $(i=1,2,3),$ for splay, twist, and bend distortion modes, as well as their ratios ${K}_{3}{/K}_{1}$ and ${K}_{2}{/K}_{1}$ are also obtained.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".