Effect of particle size of magnesium silicate filler on physical properties of paper
Bibliographic record
Abstract
Abstract Fillers are essential component of printing papers to increase the opacity, brightness, and to improve formation and printing properties. As a very little work has been reported so far on magnesium silicate (talc), the study was conducted with the filler of different particle size for papermaking. The sheets were made in the laboratory with refined mixed hardwood chemical pulp with five grades of talc, ground calcium carbonate (GCC) and precipitated calcium carbonate (PCC) fillers with 15–24% ash level. Apparent density along with tensile, burst, tear index, Z‐direction tensile strength (ZDTS) and bending stiffness index were evaluated for talc filled sheets, and compared with GCC and PCC. Physical strength properties of talc filled sheets were decreased at a faster rate on increasing filler loading in paper and decreasing the particle size of the filler. With same type of filler its particle size determines the physical properties of paper. The postulate was not found to be valid for all the three varieties of fillers viz., talc, PCC and GCC. Shape and geometry of the PCC and GCC fillers determine the individual property. © 2012 Canadian Society for Chemical Engineering
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".