Precision and Relative Bias of Automatic and Manual D 1078 Distillation
Bibliographic record
Abstract
Abstract ASTM D 1078 Distillation Range of Volatile Organic Liquids is included in the specifications for a number of organic materials used in the paint and related coatings industry, such as hydrocarbon solvents, olefinic solvents, alcohols, ketones, glycols, and esters. Historically, only manual D 1078 distillation has been used. In the last decade, however, the use of automatic distillation has become increasingly prevalent. There are fewer and fewer laboratories that use the manual method. In order to be able to incorporate automatic instruments into the present D 1078, it was necessary to establish the comparative precision and relative bias of the automatic D 1078 procedure to the manual D 1078 procedure. An interlaboratory study was conducted in the summer of 2000 involving six samples of varying distillation ranges, ten laboratories that used automatic instruments, and five laboratories that used manual instruments. The precisions for the initial boiling point, 50% boiling point, and the dry point were found to be dependent on the boiling point temperature. The precision for the distillation range was found to be dependent on the distillation range. Automatic D 1078 distillation results were found to be statistically equivalent to manual D 1078 distillation results. The average relative bias for the six samples included in the study was 0.5°C. ASTM D 1078 has been revised to reflect the new precision value and relative bias of the automatic D 1078 and the manual D 1078 distillation.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".