Cellulose
Bibliographic record
Abstract
Abstract This article covers nomenclature, sources, preparation, uses, microcrystalline cellulose, structural chemistry, reactions, solvents, and liquid crystals. Cellulose for commercial purposes comes mostly from wood and cotton, whereas cellulose for research comes from bacteria, algae, and ramie (also a textile fiber). Preparation includes pulping and purification, with an alternative method of steam explosion. The pore structure of cellulose is mentioned, along with the buildup of cellulose molecules into entire fibers. Emphasis is given to cellulose crystal structure. Recent research has provided structures with much better resolution for two crystal forms. Most native cellulose is a mixture of two crystalline phases. Cellulose solutions are important to the rayon and cellophane industries, and new solvents are of interest because they may lessen pollution and might permit commercial production of stronger cellulosic materials through the formation of liquid crystals. Figures include the chemical and physical structures of the molecule, including in solution, X‐ray diffraction patterns, the structure of a microfibril, and the unit cell structures of cellulose I–IV.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.265 | 0.233 |
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".