Bibliographic record
Abstract
Abstract The physical and chemical properties, manufacturing methods, uses, environmental concerns, and toxicity of 1,2‐dichloroethane are discussed. 1,2‐Dichloroethylene, also known as acetylene dichloride, dio‐form,α,β‐dichloroethylene, andsym‐dichloroethylene, exists in two isomers cis[156‐59‐2] and trans[156‐59‐2]. This solvent is used as an extraction solvent and as a chemical intermediate for other chlorinated solvents and compounds. The article describes the manufacturing, chemical and physical properties, storage and handling, toxicity, and its common uses. Trichloroethylene, commonly referred to as “tri”, is a widely used vapor‐degreasing solvent. In recent years its popularity has fallen mostly because of environmental restrictions on its use. Trichloroethylene has excellent solvency properties for a large number of natural and synthetic substances. This article includes physical and chemical properties, production, and use information. In addition, safety, toxicological, and environmental regulations pertinent to trichloroethylene are reviewed. Tetrachloroethylene [127‐18‐4], perchloroethylene, tetrachloroethene, commonly referred to as “perc,” is widely used in the dry‐cleaning industry as well as metal cleaning and vapor degreasing because of its excellent solvent properties. It has no flash point or flammable limits in air or oxygen. This article includes the physical and chemical properties of tetrachloroethylene, historical production within the United States, manufacturing locations and processes, as well as typical quality specifications. In addition, safety and toxicological considerations and environmental regulations pertinent to tetrachloroethylene are reviewed. The Montreal Protocol has had an impact on all of the compounds discussed in this article.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".