SASSY NMR: Simultaneous Solid and Solution Spectroscopy
Bibliographic record
Abstract
Abstract Synergism between different phases gives rise to chemical, biological or environmental reactivity, thus it is increasingly important to study samples intact. Here, SASSY (SimultAneous Solid and Solution spectroscopY) is introduced to simultaneously observe (and differentiate) all phases in multiphase samples using standard, solid‐state NMR equipment. When monitoring processes, the traditional approach of studying solids and liquids sequentially, can lead to information in the non‐observed phase being missed. SASSY solves this by observing the full range of materials, from crystalline solids, through gels, to pure liquids, at full sensitivity in every scan. Results are identical to running separate 13C CP‐MAS solid‐state and 13C solution‐state experiments back‐to‐back but requires only a fraction of the spectrometer time. After its introduction, SASSY is applied to process monitoring and finally to detect all phases in a living freshwater shrimp. SASSY is simple to implement and thus should find application across all areas of research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".