Novel Method for Quantifying Molecular Orientation by Polarized Raman Spectroscopy: A Comparative Simulations Study
Bibliographic record
Abstract
Polarized Raman spectroscopy is widely used to quantify the level of molecular orientation of various types of materials. By using a simplified procedure we call the depol (depolarization) constant (DC) method, since it assumes that the depolarization ratio is a constant. However, our ability to quantify orientation by using the DC method is often limited by the need for a completely isotropic sample showing the same chemical and phase composition as the oriented sample of interest to obtain information on the depolarization ratio. In this paper, we propose a new method for orientation quantification, the most probable distribution (MPD) method, based on the hypothesis that the population distribution is the most probable one. In contrast to the conventional DC procedure, this new method does not require knowledge of the depolarization ratio and eliminates the assumption that it does not evolve on orientation. Simulations show the wide applicability of the MPD method for large sections of the 〈P2〉 〈P4〉 diagram, especially for coordinates that are most likely to be observed in experimental conditions. They also highlight the significant inaccuracies produced by the conventional DC method due to depolarization ratio errors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".