Bibliographic record
Abstract
Abstract Cottonseed oil, America's original vegetable oil, dominated the United States vegetable oil market for over a century. Cottonseed is a by‐product of cotton and difficult to process and refine due to its unique seed structure and high content of natural pigment. Through research and experimentation, chemists have developed a clear, odorless, bland‐flavored cottonseed oil and a creamy, white shortening that set the standards for edible fats and oils worldwide. The scientific and technical advances developed to process cottonseed and cottonseed oil became the cornerstones of the edible fats and oils industry as it is known today. Numerous processes were developed or perfected especially for cottonseed oil and cottonseed which later found application for other oils and oilseeds. These processes include screw press extraction, prepress solvent extraction, and direct and expander‐solvent extraction for the crude oil; caustic and miscella refining; fractionation via winterization; deodorization; bleaching; hydrogenated basestock system; blending and formulating with various basestocks to achieve the desired performance and characteristics, etc. Today, vegetable oil processors worldwide have a wide range of raw materials to choose from, but cottonseed pioneered the American vegetable oil industry.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.097 | 0.031 |
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".