Paper mill sludge as a component of wood adhesive formulation
Bibliographic record
Abstract
Abstract Three major types of paper mill sludge, primary sludge (PS), secondary sludge (SS) and de-inking paper sludge (DPS) were characterized and evaluated as adhesive fillers. Plywood panels were made of formulations with phenol formaldehyde (PF) and sludges. Panels with PF/PS and PF/SS formulations had higher dry and wet shear strengths than those made with PF/Cocob® formulation. All wood failure values were comparable. Dry and wet shear strengths of the panels with PF/DPS formulation were comparable to those of the PF/Cocob® panels (with Cocob® as a commercial filler), but the former displayed a much lower wood failure value. Owing to this fact and its high ash content, DPS was not evaluated further as a potential component of adhesive formulations. Compared with SS, PS resulted in higher dry and wet shear strengths and higher wood failure values. However, granular SS was easier to disperse into the resin component than fibrous PS, and the PF/SS formulation was more easily dispensed on aspen veneer sheets than the PF/PS formulation. SS alone displayed adhesive properties with 0.87 MPa of dry shear strength, but PS alone did not exhibit any bond strength. PS and SS were further evaluated for their general thermal behavior and major functional groups using differential scanning calorimetry and Fourier transform infrared spectrometry, respectively.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".