Replacing Chemicals in Recycle Mills with Mechanical Alternatives. Quarterly progress report covering period October 1, 1999 to December 31, 1999
Bibliographic record
Abstract
The objective of this project is to explore potential applications of underwater pulsed power technology to the paper industry. These included fiber refining, disinfection, stickies dispersion, and stickies control. In pulsed power a spark is discharged underwater. Present commercial applications of the technology include the detonation of land mines, zebra mussel control, and water disinfection. In preliminary work the authors have found that stickies are rapidly dispersed under the influence of pulsed power. The purpose of this project is to explore other applications of the technology in the recycle paper industry, especially in applications where the technology can replace potentially expensive chemical use. The authors have found that sparking improves the screenability of stickies in the presence of pulp. Sparking is also able to detackify pitch coated on metal surfaces. This is potentially a major finding since it extends the range of the application from recycle to virgin mills. They need to determine if the effect also occurs for pitch particles suspended in whitewater. Some stickies such as Robond, a PSA used in the paint industry, are relatively unaffected by spark treatment. They find that this polymer is oxidized to a lower extent. A sparker unit has been purchased and installed at IPST. A licensing agreement with Sparktec Environmental, Stoney Creek, Canada, the manufacturer of the device, has been negotiated. It was found that sparking improves the screenability of stickies in the presence of pulp. Sparking is also able to detackify pitch coated on metal surfaces.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".