Universal and discriminative detection using a miniaturized pulsed discharge detector in comprehensive two‐dimensional GC
Bibliographic record
Abstract
A miniaturized pulsed discharge detector (Mini-PDD) has been successfully demonstrated for comprehensive 2-D GC (GC x GC) analysis of pyrolysis gasoline and the pyrolysis GC x GC analysis of a polyethylene copolymer. The detector cell volume of the Mini-PDD is reduced to 25% of the Valco plug-in PDD D-3. An n-C11 peak width at base is 96 ms for the Mini-PDD, about 23% larger than a peak width of 78 ms detected by a flame ionization detector (FID). The Mini-PDD has sufficient response time for most GC x GC applications. When Mini-PDD is operated in helium photoionization mode (Mini He-PDD), it is a universal detector for both inorganic and organic compounds. This is especially useful when detection of water is needed in GC x GC applications. When krypton is doped in the helium discharge gas (Mini Kr-PDD), it can suppress signals of compounds having higher ionization potentials and enhance relative signal intensities of aromatic compounds. The determination of aliphatic to aromatic hydrocarbon ratios is essential to the operation of petroleum crackers. Comparison of the signal from two modes of the Mini-PDD is a simple and fast way to verify the location of aromatics in comprehensive 2-D gas chromatograms.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".