Identifying the regional impact of deep thermogenic gas on aquifers in Alberta, Canada by  comparing multilayered isoscape maps of domestic water wells and fugitive gases from energy wells
Bibliographic record
Abstract
The origin and distribution of unwanted thermogenic gas in aquifers and domestic water wells in petroliferous basins are of continuing concern. Most published studies to date consider only a few water wells with little or no information on fugitive gases from nearby energy wells. We mapped δ13C of hydrocarbons in 1,124 domestic water wells and fugitive gases (many thousands) from energy wells of Alberta, Canada. About 90% of the water wells that exsolve hydrocarbons produce methane derived locally by microbes. The δ13C of these biogenic methanes vary regionally and follows topography, suggesting in situ generation of methane within a flowing aquifer perhaps following a Rayleigh constrained generation process. Some domestic water wells have free thermogenic butanes, propane and ethanes indicating the impact of thermogenic gas on the aquifer. The δ13C of these thermogenic sourced gases impacting domestic water wells matches those of nearby energy wells indicating their failure as the ultimate source of thermogenic gas in domestic water wells. The impacted water wells are geographically grouped. Our regional mapping of hydrocarbon gases in domestic water wells has identified specific, kilometre scale regions needing detailed hydrogeological and geochemical investigation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".