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Record W2900333767 · doi:10.1680/jenge.17.00003

A mass-flux method to estimate pollutants in groundwater

2018· article· en· W2900333767 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Geotechnics · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsPolytechnique Montréal
FundersDefence Research and Development Canada
KeywordsPlumeGroundwaterEnvironmental scienceContaminationAquiferPollutantHydrology (agriculture)Surface waterWater qualityDilutionFlux (metallurgy)Sampling (signal processing)Water pollutionMass fluxEnvironmental engineeringEnvironmental chemistryGeologyChemistryMeteorologyGeographyGeotechnical engineering

Abstract

fetched live from OpenAlex

Groundwater contamination is difficult to define and quantify. It may be easy or not to define who did the contamination and which contaminant was released, but it is hard to assess how much, where and when a contaminant was released. Second, concentrations fluctuate with space and time in groundwater. Third, it is difficult to assess the total mass of dissolved contaminant and the annual mass discharged into surface water or reaching pumping wells. These issues are documented with an example from Canada where the fluctuations in concentrations, over time and space, spanned four orders of magnitude within the plume. All data were examined using a quality control process, which examined all reasons for poor quality and revealed contradictory pieces of information and also poor procedures or field protocols for water sampling. An annual mass-flux method for the aquifer contaminants reaching a river was developed. It takes into account the contaminant concentration in the river and the dilution by the river water. This method helped to reconcile field and laboratory data for the mean concentrations in the plume and clarify the situation.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.006

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 head0.009
GPT teacher head0.269
Teacher spread0.259 · 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