Precision and Relative Bias of Automatic and Manual Refractometers Using ASTM D 1218 at 20°C
Bibliographic record
Abstract
Abstract The refractive index at a given temperature is an important specification parameter for a large number of petroleum products as well as various paraffinic, olefinic, and aromatic hydrocarbon solvents. It is an easy and quick test method to assure the quality and identity of a specific material. Historically, refractive index and refractive dispersion have been measured using manual refractometers. The advent of digital automatic refractometers has made the measurement of refractive index much easier. An interlaboratory study was conducted in 1996 to determine the precision of automatic refractometers and to compare the results with manual instruments. The study involved eight different samples, ten laboratories that used automatic instruments, and six laboratories that used manual instruments, using ASTM D 1218, Test Method for Refractive Index and Refractive Dispersion of Hydrocarbon Liquids, at 20°C. The repeatability of both automatic and manual refractometers was determined to be 0.0002. The reproducibility of both automatic and manual refractometers was determined to be 0.0005. The study showed that there was no statistically significant difference between results obtained with automatic and manual refractometers using ASTM D 1218 at 20°C at a 95% confidence level.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".