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Using permutational and multivariate statistics to understand inorganic well water chemistry and the occurrence of methane in groundwater, southeastern New Brunswick, Canada

2019· article· en· W2939750822 on OpenAlexafffundabout
Diana B. Loomer, Kerry T. B. MacQuarrie, Tom A. Al

Bibliographic record

VenueThe Science of The Total Environment · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of OttawaUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaIris O'Brien FoundationUniversity of New Brunswick
KeywordsGroundwaterCarboniferousMethaneGeologyDiagenesisHydrology (agriculture)SeawaterStructural basinGeochemistryEnvironmental scienceChemistryOceanographyGeomorphology

Abstract

fetched live from OpenAlex

Concerns over possible impacts from the rapid expansion of unconventional oil and natural gas (ONG) resource development prompted a regional domestic well sampling program focusing on the Carboniferous Maritimes Basin bedrock in southeastern New Brunswick, Canada. This work applies recent developments in robust multivariate statistical methods to overcome issues with highly non-Gaussian data and support the development of a conceptual model for the regional groundwater chemistry and the occurrence of methane. Principal component analysis reveals that the redox-sensitive species, DO, NO3, Fe, Mn, methane, As and U are the most important parameters that differentiate the samples. Permutation-based MANOVA and ANOVA testing revealed that geology was more important than geographic location and topography in influencing groundwater composition. The statistical inferences are supported by chemistry trends observed in relation to road de-icing salt and other saline sources. However, source differentiation between Carboniferous brines, entrapped post-glacial marine water and modern seawater cannot be made. Furthermore, Cl:Br ratios lower than those of seawater or regional brines suggest an origin related to the diagenesis of organic-rich sediment and that the groundwater may be influenced by local low permeability units. Combined spatial, statistical and chemical analysis shows that, while trace or low levels of methane, <1 mg/L, are found ubiquitously throughout the Maritimes Basin, elevated concentrations, >1 mg/L, are associated with the Horton Group, consistent with it being the host and inferred source of ONG resources in the province. The highest methane concentrations (14–29 mg/L) were detected in the region with a complex history of cycles of uplift and erosion which, in some locations, resulted in the juxtaposition at the surface of the Horton Group with several other groups of the Maritimes Basin. It is thought that proximity to the Horton Group can lead to naturally high methane concentrations in non-ONG-bearing units.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.196
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2019
Admission routes3
Has abstractyes

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