DIGITAL PRINTABILITY OF PAPERS MADE FROM INVASIVE PLANTS AND AGRO-INDUSTRIAL RESIDUES
Bibliographic record
Abstract
The use of an alternative fibre source for papermaking encourages more circular material streams with a focus on local harvesting and a lesser demand for large-scale pulping.The changes in the printing industry with the advent of digital printing technologies, such as electrophotography and ink-jet, demand that the paper should have appropriate printability.Digital printability depends on the printing machine, toner and paper.In this study, we tested six different papers made from invasive plants, namely, Japanese knotweed, black locust, Canadian goldenrod, and agro-industrial residues, such as miscanthus, tomato stems and waste jute bags.The papers were printed by electrophotography printing, and optical print quality parameters, such as optical density, printing unevenness and print gloss, as well as surface roughness and surface resistivity, were measured.The results indicate that average surface roughness and grammage have a high linear correlation with print gloss, and a moderate one with print density.The mottling values of prints have inconsistencies with the surface roughness values because of the specific fiber orientation based structure.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".