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Record W4285594795 · doi:10.1111/gwat.13227

Documentation and Prediction of Increasing Groundwater Chloride in the Twin Cities, Minnesota

2022· review· en· W4285594795 on OpenAlexaff
John R. McDaris, Joshua M. Feinberg, Anthony C. Runkel, Jonathan L Levine, Sophie M Kasahara, E. Calvin Alexander

Bibliographic record

VenueGround Water · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsHumboldt District Hospital
Fundersnot available
KeywordsAquiferBedrockGroundwaterChlorideMetropolitan areaHydrology (agriculture)Environmental scienceQuaternaryGeologyEnvironmental chemistryWater resource managementGeographyGeomorphologyChemistryArchaeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

We provide a comprehensive overview of historic chloride concentrations in the groundwater of the Twin Cities metropolitan area (TCMA) in Minnesota, in order to define the extent of chloride contamination, due primarily to the seasonal application of deicing salt to roadways. Data collected from 1278 wells between 1965 and 2020 are representative of the major aquifers underlying the TCMA and establish a regional natural background chloride concentration of less than 10 mg/L. However, 55% of all measurements (1616 of 2943) are above 10 mg/L, with the highest concentrations found within the uppermost Quaternary aquifers. Chloride concentrations in underlying bedrock aquifers are negatively correlated with the thickness and clay composition of overlying materials. Most chloride measurements (92%) remain below chronic exposure limits set by state and federal authorities. Historical trends indicate that, if the current imbalance between chloride inputs and outflows persists, chloride concentrations in TCMA aquifers will surpass regulatory thresholds by midcentury as surface waters and Quaternary aquifer waters migrate into underlying bedrock aquifers. Most wells in this study are monitored annually, making it impossible to detect important sub-annual fluctuations of chloride concentration that can exceed 40%.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.248
Teacher spread0.220 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2022
Admission routes1
Has abstractyes

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