Asphaltene Content Measurement Using an Optical Spectroscopy Technique
Bibliographic record
Abstract
A new spectrophotometry technique for quantifying the asphaltene content of black oil samples improves data quality, reduces measurement time, and reduces solvent volume in comparison with conventional methods. According to this method, asphaltenes are quantified by subtracting the visible spectrum of the maltenes from that of the oil. We found that the difference in spectra of oil and maltenes correlated well with the modified ASTM D6560 method for a large sample set that covered a wide range of geographic locations, which points to the existence of a global correlation between the visible spectrum of asphaltenes and their concentration. The repeatability of the measurements, even for low-asphaltene samples, was far better than that achieved with conventional methods. The measurement time was reduced to less than 3 h from 2 days in conventional measurements, and the solvent volume was reduced from 250 mL using the conventional technique to 40 mL using the optical method, thereby reducing the environmental footprint of the measurement.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".