Geochemistry of Naturally Occurring Methane from Two Canadian Case Studies
Bibliographic record
Abstract
Increased unconventional hydrocarbon production in the United States and Canada piqued interest in natural gas development, while simultaneously raising concerns regarding changing groundwater quality following hydrocarbon extraction. Adequate characterization of baseline groundwater geochemistry preceded hydrocarbon production in many areas. This study, based in the relatively undeveloped St. Edouard region of Quebec, Canada, and the moderately developed McCully gas field of New Brunswick, Canada, attempts to characterize naturally occurring hydrocarbon geochemistry prior to unconventional energy development. Specifically, I focus on characterizing the composition and origins of hydrocarbons and salts in regional groundwater in these areas. Eighteen samples were collected (eleven from St. Edouard and seven from McCully) and analyzed for hydrocarbon concentrations and hydrocarbon stable isotopic composition, major gas concentrations, noble gas elemental abundance and isotopic concentrations, tritium concentrations and dissolved ion concentrations. The data suggests that hydrocarbons represent a mixture of thermogenic natural gas and biogenic methane likely formed by primary and secondary biogenesis; noble gas geochemistry supports these conclusions. The ionic composition of water is consistent with a diluted brine associated with the thermogenic hydrocarbon gases that also showed signs of post genetic alteration via hydrocarbon oxidation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".