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Record W2982135098 · doi:10.4095/222772

Digital surficial geology data of the Greater Toronto and Oak Ridges Moraine area, southern Ontario

2006· report· en· W2982135098 on OpenAlexaffabout
D R Sharpe, P J Barnett, T A Brennand, G Gorrell, H A J Russell

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsMoraineGeological surveyGeologic mapGeologyArchaeologyChristian ministryCartographyPhysical geographyGeographyGeomorphologyGlacierPaleontology

Abstract

fetched live from OpenAlex

This CD-ROM digital release contains digital files for the surficial geology of the Greater Toronto and Oak Ridges Moraine areas. The data on this CD-ROM has been released previously as hardcopy Geological Survey of Canada Open File 3062. Additionally, all of the 1:50 000 scale mapsheets in this release have been released in hardcopy format by either the Geological Survey of Canada or Ontario Geological Survey. New mapping was completed for the nine mapsheets within the NATMAP study area. This re-mapping is based on new field work complemented by archival field data. Combined most maps have > 1,000 field sites. The six maps outside the NATMAP area have been re-mapped with a minimum of new fieldwork but include re-assessed archival data and a simple common legend. The summary map here retains the linework, legend, and many of the symbols of the 1:50 000 map series. The geology coverage on this CD-ROM is provided in a variety of vector formats (E00, Shape, MapInfo). This CD-ROM does not contain any base information from Geomatics Canada National Topographic Database. The Oak Ridges Moraine NATMAP and Hydrogeology Project has been a collaborative geoscience project with the Ontario Geological Survey, Ontario Ministry of Environment and the Ontario Ministry of Natural Resources.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.032
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.006

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 head0.051
GPT teacher head0.240
Teacher spread0.189 · 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

Citations7
Published2006
Admission routes2
Has abstractyes

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