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Record W2914309168 · doi:10.4095/313579

The Ambient Groundwater Geochemistry Program: northeastern Ontario pilot project

2019· report· en· W2914309168 on OpenAlexaboutno aff
K M Dell

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsnot available
Fundersnot available
KeywordsGroundwaterGeologyGeochemistryEnvironmental scienceGeotechnical engineering

Abstract

fetched live from OpenAlex

A northern Ontario component of the Ambient Groundwater Geochemistry Program (AGGP) was initiated to determine if the methods employed in this project in southern Ontario could be successful in delineating the effect of Precambrian host rock lithology on groundwater chemistry. This third season of the AGGP in northern Ontario was completed in 2018 in the North Bay area and follows two others in 2016 in Sudbury and 2017 along the north shore of Lake Huron and Manitoulin Island. Together, they provide a broad band of samples across north central Ontario at a relatively uniform density. In total, 105 overburden and 337 bedrock wells were sampled and analyzed for metals, anions, bacteria, nitrogen parameters, tritium, ?2H and ?18O, and radionuclides. With the 2018 project in North Bay, a sufficient sample density and distribution exists to create a detailed characterization of groundwater trends across northeastern Ontario. This poster illustrates some of the regional trends and groundwater characteristics observed in the northern Ontario AGGP data thus far. Our preliminary interpretation suggests that groundwater geochemistry is influenced by host lithology, hydrogeological flow conditions, drift thickness and drift composition. The Precambrian geologic province from which the groundwater originates may be a factor controlling certain regional variations in groundwater chemistry that have been observed. Samples collected from Southern Province rocks of the Huronian Supergroup and the Sudbury Basin show relatively high Co, As, Pb and Cu concentrations versus the Grenville Province. However, preliminary interpretation of some parameters also reveals anomalies coincident with surficial geologic features. In the North Bay area, wells completed in bedrock with overlying Pleistocene clay yield groundwater with higher concentrations of TKN and NH4. These may have originated from the overlying clays because of breakdown of proteinaceous organic matter within the clay. Areas with overlying clay units also have higher gross beta concentrations which may be caused by an enrichment of the naturally occurring 40K isotope in the clays. Ratios of Cl-Br show a subset of samples with a measurable influence from deep brine water and another subset where surface contamination is indicated; either from road salt or septic sources. Groundwater samples indicating brine mixing have higher Li, Ca, F- and Br- concentrations suggesting longer residence times in the aquifer; and this is supported by lower average tritium (half life = 12.3 years) content. Preliminary interpretation of the 2016 and 2017 data indicate that radon in water is controlled by availability of uranium in the host aquifer. Uranium concentrations, on the other had, are controlled by redox conditions and ion complexing and may not have a strong relationship with uranium concentration in the rocks. Future work will seek to further characterize the controls on groundwater chemistry, employing tools such as multivariant analysis and sulphur and strontium isotopes to trace the sources of solutes.

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)0.003
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.029
GPT teacher head0.278
Teacher spread0.248 · 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
GenreOther

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

Citations1
Published2019
Admission routes1
Has abstractyes

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