Fast supercritical fluid chromatography hydrocarbon group-type separations of diesel fuels using packed and monolithic columns
Bibliographic record
Abstract
Two approaches for decreasing diesel hydrocarbon group-type separation times by normal phase supercritical fluid chromatography (SFC) are compared. Short (10-15 cm) columns with small 3 microm diameter packing are compared with monolithic Chromolith bare silica columns under high carbon dioxide flow rates approaching 5 ml min(-1). Elution times are reduced up to 13-fold on a 10 cm Chromolith column and 7-fold on the short packed columns compared with conventional length columns run at typical flow rates. Short packed columns, with their higher surface area and retention characteristics, offer higher resolutions compared with Chromolith columns. Diesel samples are separated into saturates, mono-, di-, tri-, and polyaromatics in as little as 2 min on a 10 cm packed silica column. Diesel group-type results on a 15 cm titania-silica coupled column compare favorably with results from longer columns.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".