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Record W2981718324 · doi:10.4095/297739

A three dimensional surficial stratigraphic model for southern Ontario

2016· report· en· W2981718324 on OpenAlexaffabout
H A J Russell, Andy F. Bajc, A K Burt, C Logan, R Muligan, D R Sharpe

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeologyGeological surveyAquiferBoreholeGeologic mapHydrology (agriculture)ArchaeologyGeomorphologyGeographyPaleontologyGroundwater

Abstract

fetched live from OpenAlex

Over the past ten years, the Ontario Geological Survey has completed extensive subsurface investigations in and beyond the Greater Golden Horseshoe region of southern Ontario to support development of regional 3-D surficial geological models (e.g., Waterloo, Oro). The combined efforts of this work and that of the Geological Survey of Canada over the Oak Ridges Moraine Area, has resulted in close to 50% of the total area of southern Ontario being modelled. Following the extensive work associated with the development of Source Water Protection Plans, there is now a need, and value, in developing a regional surficial geological framework for all of Southern Ontario. To develop a framework for a regional 3-D model, multiple components are being worked on that include, i) development of a simplified legend of hydrostratigraphic units, ii) identification of a conceptual model to ensure appropriate reconciliation of legend items both stratigraphically and architecturally, iii) compilation of an index stratigraphic framework of continuously cored boreholes, including borehole geophysics and seismic data, iv) quality control of the MOECC water well data, v) stratigraphic coding of the water well records, and vi) interpolation of an integrated, fully attributed 3-D model of regionally significant aquifer and aquitard units. This multiyear initiative is anticipating a preliminary model in 2018 with full documentation and final products available by 2019.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.586
Threshold uncertainty score0.992

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.079
GPT teacher head0.245
Teacher spread0.166 · 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 designSimulation or modeling
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
Published2016
Admission routes2
Has abstractyes

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