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Record W6940685991 · doi:10.11575/prism/26899

Microbial Communities Associated with Hydraulic Fracturing Fluids from Shale Gas Fields in Western Canada

2015· other· en· W6940685991 on OpenAlexfundaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2015
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaGenome AlbertaAlberta InnovatesShellShell Global Solutions InternationalSuncor Energy IncorporatedConocoPhillipsGenome Canada
KeywordsHydraulic fracturingMicrobial population biologyBiomass (ecology)Natural gasFracturing fluidShale gasOil shaleMethane

Abstract

fetched live from OpenAlex

Hydraulic fracturing has revolutionized the natural gas industry and has become a prominent process in Western Canada. Since its introduction to Canada in 2005 no work regarding the associated microbial communities has been conducted. Microbes are introduced with the fracturing fluid during fracturing. Early flowback water has increased microbial biomass relative to the fracturing fluid. As flowback proceeds physicochemical conditions become increasingly saline and there is a rapid decrease in biomass. The microbial community changes reflect the changing conditions with a decrease in diversity and abundance. Community composition shifts accordingly from one resembling the source water to a halophilic community that is more adapted to the flowback water conditions. The lack of thermophiles indicates that temperature is the limiting factor that accounts for low amounts of biomass. This indicates that microbial activity will not negatively impact hydraulic fracturing operations.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.010
GPT teacher head0.159
Teacher spread0.149 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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