Drop forming as a basis for scaling up of the in situ coating process
Bibliographic record
Abstract
Abstract Cutting the costs of tablet manufacture is one of the many advantages melt crystallization offers as a technology for producing pharmaceutical coated tablets, compared to conventional tableting procedure. Other advantages include the lower number of steps needed for production, which increases productivity; the lower energy and workforce requirements; and the decreased need for stricter post‐production quality control measures while maintaining quality. The scientific term for maintaining quality is ensuring the reproducibility of experimental results. The main focus of this study is to scale up the drop‐forming process of coating, in this case of ibuprofen tablets using Lutrol. The main emphasis therefore focuses on transferring the respective optimized conditions that work for the respective system onto the industrial device. This results in the production of tablets with consistent quality in terms of geometry and coat purity. This goes in hand with the extensive modifications applied to the device for the purpose of process scale‐up. The final outcome is represented in a scaled‐up production of the coated pharmaceutical tablets through the process of melt crystallization, the reproducibility of which as a tablet manufacturing method is also proven.
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 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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".