Second-Dimension Temperature Programming System for Comprehensive Two-Dimensional Gas Chromatography. Part 1: Precise Temperature Control Based on Column Electrical Resistance
Bibliographic record
Abstract
A second-dimension temperature programming system ( 2 DTPS) for comprehensive two-dimensional gas chromatography (GC × GC) is introduced, and its performance is characterized. In the system, a commercial stainless-steel capillary column was used for the separation, as a heating element, and as a temperature sensor. The second dimension ( 2 D) column was resistively heated and controlled using an Arduino Uno R3 microcontroller. Temperature measurement was accomplished by measuring the overall 2 D column’s electrical resistance. A diesel sample was used to compare the 2 D peak capacity ( 2 n c ) and resolution ( 2 R s ), while a perfume sample was used to compare the reproducibility of the system for within-day ( n = 5) and day-to-day ( n = 5) results. The 2 n c improved by 52% with the 2 DTPS compared to the secondary oven. The GC × GC system utilizing the 2 DTPS had an average within-day and day-to-day relative standard deviation (RSD) of 0.02 and 0.12% for the 1 D retention time ( 1 t R ), 0.56 and 0.58% for the 2 D retention time ( 2 t R ), and 1.18 and 1.53% for the peak area, respectively.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".