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Record W2965615177 · doi:10.1139/cjes-2018-0080

Salt anomalies in potash beds of the Esterhazy Member, Devonian Prairie Evaporite Formation, Saskatchewan, Canada

2019· article· en· W2965615177 on OpenAlexaffvenueabout
David Edward Cisyk

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsPotashCorp (Canada)
Fundersnot available
KeywordsEvaporiteGeologyHaliteDevonianPotashGeochemistryCarbonateAnhydriteSedimentary rockPaleontologyGypsumPotassium

Abstract

fetched live from OpenAlex

The Esterhazy Member of the western Canada Prairie Evaporite has been mined underground for sylvite (KCl) since the early 1960s. Although the geology of the Esterhazy Member ore body is largely considered a regional flat lying continuous series of thin potash hosting beds, there are numerous occurrences where the ore has been either replaced or removed leaving behind uneconomical halite-rich sections. An explanation of the underlying controls on the formation of these salt anomalies has been somewhat elusive although the overwhelming assumption remains that these features developed in lows on a salina. This paper proposes that salt anomalies formed because of two processes, early compaction of carbonate shoals of the Winnipegosis Formation and tectonics that resulted in multiple stages of block movement during the deposition of the upper Prairie Evaporite. Since these two processes can result in a significantly different size to a salt anomaly, encountering one or the other type can have a significant effect on the economics of the ore body. This paper looks at some of the geological methods that might provide geologists with means to predicting salt anomalies.

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 score0.031
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.183
Teacher spread0.174 · 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

Citations4
Published2019
Admission routes3
Has abstractyes

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