Chemical Composition of Athabasca Bitumen: The Saturate Fraction
Bibliographic record
Abstract
Presented is an account of the bulk and molecular composition of the saturate fraction of Athabasca bitumen. It is shown that, for a clean isolation, it is necessary to subject the column-chromatography-separated crude saturates to molecular distillation followed by a silver ion chromatography step. Upon field ionization mass spectrometry (FIMS) analysis, the molecular distribution of the purified saturates exhibits a pulsating character with near trace concentration at hexa- and heptacyclics and varying concentrations of mono- to pentacyclics, with bi-, tri-, and tetracyclic dominance. The overall distribution is bimodal and, in contrast to conventional gas chromatography (GC) or GC−mass spectrometry (MS) results, extends to m / z ∼750, having maxima at m / z ∼400 and 600, with a total concentration of 15.1% of the bitumen. A gamut of biomarker molecules has been identified, including drimanes, cheilanthanes, tetracyclic terpanes, 17,21- and 8,14-secophanes, steranes and diasteranes, hopanes, gammaceranes, hexahydrobenzohopanes, etc. GC−FIMS results indicate that over half a dozen isomers accompany nearly each of the identified biomarkers. Although biomarker chemistry lies outside the scope of the present paper (an item that will be dealt with in detail in a forthcoming paper), we briefly remark here that the overall distribution of the biomarkers detected is consistent with and thus lends support to the notion that Athabasca bitumen is the residue of the secondary microbiological degradation of mature/(early mature) marine carbonate oils formed in a strongly reducing depositional environment. Additionally, a useful novel method for the extraction of biomarkers from oil sands is reported.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".