MétaCan
Menu
Back to cohort
Record W2982011518 · doi:10.4095/295179

Shallow drilling and piezometer installations near Killarney, Manitoba for hydrogeological investigations of the Spiritwood Buried Valley Aquifer

2014· report· en· W2982011518 on OpenAlexaffabout
M J Hinton, D R Sharpe

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsPiezometerBoreholeDrillingGeologyAquiferGeological surveyHydrogeologyGroundwaterHydrology (agriculture)Geotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

The Geological Survey of Canada (GSC) is investigating the hydrogeology of the Spiritwood buried valley aquifer in southwestern Manitoba as part of its Groundwater Geosciences Program. This Open File reports on a drilling program conducted in November 2010 in which one shallow and one intermediate depth piezometer were installed within separate boreholes at each of three sites near Killarney, Manitoba to complement existing deep wells monitored by Manitoba Conservation and Water Stewardship (Government of Manitoba, Ministry of CWS). Boreholes were advanced without drilling fluids by the cable tool method and by driving core tubes which allowed for accurate borehole logging and the collection of sample cores at selected depths. This Open File includes the geological logs of the boreholes, the piezometer construction details and the geotechnical data measured on sampled core. Geotechnical analyses included measurement of approximate shear strength using a pocket penetrometer (n=21), grain size distribution (n=8), gravimetric water content (n=91), and wet bulk density (n=22) from which dry bulk density (n=22) and volumetric water content (n=22) were calculated and porosity (n=22) estimated. The drilling program was a collaborative effort between the Agri-Environmental Services Branch (AESB) of Agriculture and Agri-Food Canada (AAFC) and the Geological Survey of Canada of Natural Resources Canada (NRCan).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.049
GPT teacher head0.271
Teacher spread0.222 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2014
Admission routes2
Has abstractyes

Explore more

Same topicGeophysical Methods and ApplicationsFrench-language works237,207