Permittivity of Naphthenic Acid-Water Mixture
Bibliographic record
Abstract
Naphthenic acid (NA) is predominantly a mono-carboxylic acid obtained as a by-product of petroleum refining with variable composition and ingredients. It is reported that water affected by processes in the petroleum industries generally contains 40-120 mg IL of naphthenic acid which is considered to be in the range of toxicity to human consumption [Clemente et. al, 2005; McMartin, 2003]. This contaminated water needs treatment before its use as drinking water by remote communities. Recent literature suggests that NAs could be separated from diesel fuel using microwave radiation [Lingzhao et. al, 2004]. Removal of naphthenic acid from vacuum cut #1 distillate oil of Daqing using microwaves has also been reported by Huang et. al [2006]. The microwave treatment can be applied to drinking water containing small concentrations of naphthenic acid. In this case permittivity information is useful in designing a microwave applicator and modeling studies. Permittivity measurements were done using a HP 8510 Vector Network Analyzer and coaxial probe reflection method to study the dielectric properties of naphthenic acid in water. The effects of process variables such as frequency, concentration and temperature on dielectric properties were determined.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".