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Record W2981440638 · doi:10.4095/226194

Hydrogeological regions of Canada: Data release

2008· report· en· W2981440638 on OpenAlexaffabout
D R Sharpe, H A J Russell, Stephen E. Grasby, P R J Wozniak

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsPhysiographic provinceGeologyHydrogeologyGroundwater rechargeBedrockGroundwaterPermafrostTerrainElevation (ballistics)Groundwater flowLandformHydrology (agriculture)Structural basinGeomorphologyAquiferGeographyCartography

Abstract

fetched live from OpenAlex

The Hydrogeological Regions Map depicts first order regions of Canada that have distinct groundwater systems. The country is assigned to nine regions as determined by frozen ground, geology, and physiography. Frozen ground has a dominant affect in the continuous permafrost region and the southern limit of this region cuts across both physiographic and geological features. Geology controls surface expression of the landscape and subsurface water-bearing characteristics, and the bedrock contacts that delineate geological terrains and basins represent the major region boundaries. Physiographic features are influenced by geology and coincide closely with geological boundaries but also divide geological units where elevation dominates, primarily along the eastern limit of the Cordillera. Physiographic features provide hydraulic gradients for regional and local flow and combine with climatic and run-off characteristics to dictate the regional moisture surplus or deficit that affects recharge to and discharge from groundwater systems. Moisture index isolines based on the Thornthwaite classification overlay the regions to provide a sense of moisture deficiency or surplus.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.031
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.016
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0310.011

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 head0.201
GPT teacher head0.282
Teacher spread0.081 · 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

Citations1
Published2008
Admission routes2
Has abstractyes

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