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Record W2188824577 · doi:10.4095/213689

Using downhole geophysical logs to provide detailed lithology and stratigraphic assignment, Oak Ridges Morain, southern Ontario

2002· report· en· W2188824577 on OpenAlexaffabout
S E Pullan, J. A. Hunter, R L Good

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeologyLithologyGeophysicsPaleontologySeismologyGeomorphology

Abstract

fetched live from OpenAlex

In a regional hydrogeology study, Oak Ridges Moraine area, southern Ontario, downhole geophysical logs from 11 deep (about 90.190 m), plastic-cased, continuously logged boreholes helped establish these sites as high-quality stratigraphic benchmarks. Acquired logs include natural gamma, conductivity, magnetic susceptibility, spectral gamma, temperature, and seismic velocity measurements. The downhole logs provide detailed physical properties (at submetre to metre scale) that aid in lithological characterization and in determining subsurface stratigraphy. While natural gamma, conductivity, and magnetic susceptibility logs are useful to identify varied lithological units downhole, they cannot be used alone to differentiate the Newmarket Till (a regionally significant aquitard) from overlying or underlying units. However, this till is characterized by seismic velocities (>2500 m/s) that are significantly higher than most other sediments encountered in these boreholes. Seismic velocities also show promise as a porosity indicator and spectral gamma logs provide relative density estimates.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.075
GPT teacher head0.298
Teacher spread0.224 · 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 designObservational
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

Citations8
Published2002
Admission routes2
Has abstractyes

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