Bibliographic record
Abstract
Tranexamic acid is an antifibrinolytic agent that inhibits the conversion of plasminogen to plasmin and is used to treat fibrinolytic hemorrhages. Tranexamic acid mouth rinse was compounded using active pharmaceutical ingredient powder or commercial tablets. The bitter taste was masked by using either cherry-vanilla or peppermint and mint flavoring and aspartame. Tranexamic acid mouth rinse solutions were stored at either 23°C or 5°C in polyethylene terephthalate bottles for 31 days. Stability was accessed using a stability-indicating high-performance liquid chromatographic method. Color, clarity, caking, resuspendability, and pH were also monitored. All solutions remained above 97.2% of the initial concentrations after 31 days storage at either 23°C or 5°C and protected from light. The powder-based solutions remained clear, and no color change was observed. However, some of the tablet formulations stored at 23°C turned yellow to dark brown after 21 days. Insoluble material from the tablet formulations settled out but was easy to resuspend with no caking. The pH of the tranexamic acid mouth rinse solutions changed slightly over the course of the study. All tranexamic acid mouth rinse solutions were chemically stable for 31 days when stored at either 23°C or 5°C and protected from light.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".