An Added Dimension: GC Atmospheric Pressure Chemical Ionization FTICR MS and the Athabasca Oil Sands
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Athabasca oil sands industry, an alternative source of petroleum, uses large quantities of water during processing of the oil sands. In keeping with Canadian environmental policy, the processed water cannot be released to natural waters and is thus retained on-site in large tailings ponds. There is an increasing need for further development of analytical methods for environmental monitoring. The following details the first example of the application of gas chromatography atmospheric pressure chemical ionization Fourier transform ion cyclotron resonance mass spectrometry (GC-APCI-FTICR MS) for the study of environmental samples from the Athabasca region of Canada. APCI offers the advantages of reduced fragmentation compared to other ionization methods and is also more amenable to compounds that are inaccessible by electrospray ionization. The combination of GC with ultrahigh resolution mass spectrometry can improve the characterization of complex mixtures where components cannot be resolved by GC alone. This, in turn, affords the ability to monitor extracted ion chromatograms for components of the same nominal mass and isomers in the complex mixtures. The proof of concept work described here is based upon the characterization of one oil sands process water sample and two groundwater samples in the area of oil sands activity. Using the new method, the Ox and OxS compound classes predominated, with OxS classes being particularly relevant to the oil sands industry. The potential to resolve retention times for individual components within the complex mixture, highlighting contributions from isomers, and to characterize retention time profiles for homologous series is shown, in addition to the ability to follow profiles of double bond equivalents and carbon number for a compound class as a function of retention time. The method is shown to be well-suited for environmental forensics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it