A preparative method for the isolation and fractionation of dissolved organic acids from bitumen-influenced waters
Bibliographic record
Abstract
The surface mining of oil sands north of Fort McMurray, Alberta produces considerable tailings waste that is stored in large tailings ponds on industrial lease sites. Viable strategies for the detoxification of oil sands process affected water (OSPW) are under investigation. In order to assess the toxic potential of the suite of dissolved organics in OSPW, a method for their extraction and fractionation was developed using solid phase extraction. The method successfully isolated organic compounds from 180 L of an aged OSPW source. Using acidic- or alkaline-conditioned non-polar ENV+ resin and soxhlet extraction with ethyl acetate and methanol, three fractions (F1-F3) were generated. Chemical characterization of the generated fractions included infusion to electrospray ionization ultrahigh-resolution mass spectrometry (ESI-UHRMS), liquid chromatography quadrupole time-of-flight mass spectrometry, gas chromatography triple quadrupole time-of-flight mass spectrometry, and synchronous fluorescence spectroscopy (SFS). Additionally, ESI-UHRMS class distribution data and SFS identified an increased degree of oxygenation and aromaticity, associated with increased polarity. Method validation, which included method and matrix spikes with surrogate and labelled organic mono carboxylic acid standards, confirmed separation according to acidity and polarity with generally good recoveries (average 76%). Because this method is capable of extracting large sample volumes, it is amenable to thorough chemical characterization and toxicological assessments with a suite of bioassays. As such, this protocol will facilitate effects-directed analysis of toxic components within bitumen-influenced waters from a variety of sources.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".