Influence of fibre length and filler particle size on pore structure and mechanical strength of filler‐containing paper
Bibliographic record
Abstract
Abstract Test sheets were prepared by incorporating softwood pulp with silica filler, PW‐5 (diameter 4.5 μm) or PW‐20 (15 μm). Length‐weighted averages of fibre were 2.5 (uncut fibre) and 1.25 mm (short‐cut fibre). Pore sizes less than 150 urn were measured by mercury porosimeter. Sheets of short‐cut fibres and mixed with uncut fibres at ratio of 3:1 or 1:3 had larger pore volumes than others tested. When filler content increased, the total pore volume increased for PW‐20 sheets, but it did not for PW‐5 sheets with short‐cut fibres. Tensile index and folding endurance were very much affected by fibre length. Contact number on a fibre was calculated by computer simulation, and it had a linear relation with tensile index of sheet.
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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".