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Record W2791538377 · doi:10.4095/306571

Highlights of OGS-GSC collaboration on regional groundwater studies: 2017-2018

2018· report· en· W2791538377 on OpenAlexaffabout
H A J Russell, R D Dyer

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGroundwaterEnvironmental scienceGeographyGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

The Ontario Geological Survey and Geological Survey of Canada groundwater collaboration in Southern Ontario is finishing the fourth year of a five year project cycle ending March 31st 2019. Following earlier updates on work completed this summary will be provided under five principal themes. 1. Framework for Sustainable Groundwater Use: The 3D bedrock modelling activity has developed the 5th iteration of the formation level working model. Final QA/QC is being completed during the winter of 2018. An animation on the salient features of the model and viewing options was published. The surficial modelling work has been delayed due to efforts on the bedrock model; however progress is underway and iterative QA/QC on a preliminary 8 layer model is progressing. 2. Supporting Great Lakes Water Accords: Work has advanced on development of a conceptual framework for evaluating groundwater - surface water interactions and impacts on the quality and quantity of water and ecosystems. A contract was awarded for a fully coupled regional numeric groundwater - surface-water "proof-of-concept" model for southern Ontario in the Hydrogeosphere modelling environment. 3. Methods Development for Regional Groundwater Studies: Methods are being advanced through analysis of seismic reflection data processing, and downhole geophysics. A new initiative this year was preliminary work with Nuclear Magnetic Resonance tools. Progress continues on regional methods for soil moisture studies using RadarSat II and SMOS. Work was initiated on a hydrogeophysical study over part of the Vars-Winchester esker to explore the potential extrapolation of hydraulic parameters using high-resolution multi-component seismic data and electrical resistivity data. 4. Case Studies: Data collection has been completed in a number of areas. Sample analysis for the chemostratigraphic framework using samples from continuous core has been expanded to include Dundas Valley, Brantford, and London. A geostatistical approach is being applied to develop a hydraulic parameter estimation for a 3D model of the Innisfil Creek sub-watershed. Characterization of Newmarket Till cementation is ongoing and is being supplemented by porewater chemistry analysis. A range of data consolidation work has been advanced on GSC, OGS datasets and technical reports related to municipal wells and aquifers contributed by conservation authorities. Work is ongoing on the hydrostratigraphic classification of wells within the PGMN with most monitors screened in surficial deposits having received a preliminary classification. 5. Science and Technology Exchange: Manuscript submission is finished for a special issue of Canadian Journal of Earth Sciences with 8 published articles and 3 manuscripts in review. Project results are available via OGS - GSC publication streams, conference proceedings, and journal publications. Three overview documents on bedrock modelling, chemostratigraphy, and data consolidation were published in the Ontario Geological Survey Report of Field Work and Other Activities for 2017.

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)0.015
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.359
Threshold uncertainty score0.723

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0040.002
Scholarly communication0.0080.003
Open science0.0030.011
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0570.014

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 head0.071
GPT teacher head0.320
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2018
Admission routes2
Has abstractyes

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