Nondestructive Multicomponent Terahertz Chemical Imaging of Medicine in Tablets
Bibliographic record
Abstract
Molecular networks based on noncovalent bonds have resonant frequencies in the terahertz (THz) region. THz spectroscopy is a powerful tool for identifying molecular bonds, such as intermolecular or intramolecular hydrogen bonds, in pharmaceuticals. A THz chemical imaging (TCI) system was developed by combining a THz time-domain spectrometer with a translational stage to obtain two-dimensional distributions of molecular networks in tablet samples. Since THz spectral peaks of pharmaceuticals are broad at room temperature, multicomponent chemical analysis with the TCI system has some limitations. In this paper, we describe multicomponent chemical analysis of pharmaceuticals using a sample chamber cooled by a cryostat. TCI measurement at low temperature sharpens spectral peaks and/or shifts peak frequencies, enabling us to determine the distribution of several kinds of pharmaceuticals in a tablet. The TCI system provides THz images of polymorphic form distribution of famotidine binding with D-mannitol in an over-the-counter pharmaceutical tablet. Furthermore, the molecular mechanics method was used to determine the vibrational modes of the peaks in the spectra of famotidine polymorphic forms.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".