Bibliographic record
Abstract
The interactions between cellulose nanocrystals and six different polymers (three anionic, two non-ionic, and one cationic) were investigated using rheological measurements of aqueous solutions of nanocrystals and polymers. The experimental viscosity data could be described adequately by a power-law model. The variations in power-law parameters (consistency index and flow behavior index) with concentrations of nanocrystals and polymers were determined for different combinations of nanocrystals and polymers. The interactions between nanocrystals and the following polymers: anionic sodium carboxymethyl cellulose and non-ionic guar gum, were found to be strong in that the consistency index increased substantially with the addition of nanocrystals to polymer solutions. The interaction between nanocrystals and non-ionic polymer polyethylene oxide was moderate. Depending on the concentrations of nanocrystals and polymer, the consistency index both increased and decreased upon the addition of nanocrystals to polymer solution. The interactions between nanocrystals and the following polymers: anionic xanthan gum, anionic polyacrylamide, and cationic quaternary ammonium salt of hydroxyethyl cellulose, were found to be weak. The changes in rheological properties with nanocrystal addition to these polymer solutions were found to be small or negligible.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".