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Record W2990419582 · doi:10.4095/315045

A three-dimensional geological model of the Paleozoic bedrock of southern Ontario

2019· report· en· W2990419582 on OpenAlexaffabout
Terry R. Carter, F R Brunton, J K Clark, L Fortner, C Freckelton, C Logan, H A J Russell, M.L. Somers, L Sutherland, K Yeung

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsPaleozoicBedrockGeologyPaleontologyGeomorphology

Abstract

fetched live from OpenAlex

A regional three-dimensional (3-D) lithostratigraphic model of the Paleozoic bedrock of southern Ontario has been completed. The model encompasses the entire Phanerozoic succession of southern Ontario (110 000 km2), consisting of over 1500 m of sedimentary strata straddling regional arch, or forebulge, zones separating the Appalachian foreland basin from the Michigan structural basin. This initiative provides an unprecedented regional 3-D perspective and digital framework based on an updated regional lithostratigraphic chart. Constructed using Leapfrog Works, an implicit modelling software application, the model format can readily support numeric groundwater-flow modelling. Fifty-four Paleozoic bedrock layers representing 70 formations, as well as the Precambrian basement and overlying unconsolidated sediment, were modelled at a spatial resolution of 400 m. Borehole records in Ontario's public petroleum well database (Ontario Petroleum Data System (OPDS)) were the principal data source, supplemented by Ontario Geological Survey (OGS) deep boreholes, measured sections, control points and Michigan boreholes. A newly revised digital bedrock topography surface combined with revised subcrop geology and digitized 3-D surface polyline and point constraints were used to better align the modelled layers and their extrapolation to the subcrop surface. Model development was an iterative cycle of interim modelling, expert geological appraisal, and quality assurance and control (QA/QC) editing of geological data using geophysical logs, drill cuttings and core, supplemented by manual editing of model layers. The 3-D model provides a robust representation of regional bedrock geology. A properly constructed borehole database and its supporting information is an essential requirement for construction of a 3-D model, but data errors, inconsistencies, data gaps, location errors, etc. can compromise the reliability of the model. From 2015 to 2018, project geologists and geological contract staff of the Oil, Gas and Salt Resources Library completed edits to 30 320 formation tops in a total of 7812 wells, resulting in a revised data set and permanent improvements to the petroleum well database. This report highlights the importance of QA/QC of well data, specifically formation top identification, and summarizes the data improvements made in support of the present 3-D model. No seismic data was available.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.055
GPT teacher head0.222
Teacher spread0.167 · 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 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

Citations10
Published2019
Admission routes2
Has abstractyes

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