Bibliographic record
Abstract
Printing is important to industries, schools, libraries and homes. Hence, it is important to investigate and develop eco-friendly methods for printing inks. In the food industry, one of the wastes is used frying oil, which can be epoxidized and polymerized to produce binders in printing ink. Another method is to utilize epoxidized soybean oil as a UV-curable acrylate oligomer via cross-linking in order to be repurposed as a binder. Both of these solutions could prevent solvent emissions, reduce pollution or waste, help regulating harmful organic materials and replacing unsustainable petroleum-based printing inks. In terms of chemical synthesis, scholars have suggested that resin precursors for lithographic inks could employ low-molecular soy oil-based rosin esters. Next, the esters are cross-linked through radical polymerization, which is induced by heat along with radical initiators like peroxides. Peroxides allow the ink to dry instantly, which is desired in printing process. Finally, the sustainable inks could be sold to printer companies, newspaper companies, advertising companies and consumers for a cheaper price with lower production costs. Faculty Mentor: Samuel Mugo Department: Chemistry
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.019 |
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".