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Record W4405098607 · doi:10.22215/etd/2024-16226

Integrity of Drilling Waste Sumps, Mackenzie Delta Area, NT

2024· dissertation· en· W4405098607 on OpenAlexfundno aff
Rachelle Nicole Landriau

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaAurora Research Institute
KeywordsDeltaDrillingEnvironmental scienceTetrachloroethyleneGeologyEngineeringPetroleum engineeringEnvironmental chemistryTrichloroethyleneChemistryMechanical engineering

Abstract

fetched live from OpenAlex

n 1960–2005, over 220 sumps were constructed in Mackenzie Delta and adjacent uplands to contain used drilling muds within permafrost. Past records were compared with current field data at 12 sites to investigate egress of contaminants from the sumps under a warming climate. Electromagnetic surveys by EM-31 determined ground conductivity fields on and off the sumps. These surveys were complimented by ICP-MS analysis of soil samples to determine concentrations of Na, Cl and K at the sites. Three sites, one in the uplands and two in the delta appeared to be holding the saline fluids in place; elsewhere there was little difference in conductivity on and off the sumps. The principal contributor to the performance of these sumps was age. Younger sumps showed a distinct region of elevated conductivity near the center of the sump, whereas the older features had similar conductivity on the sump and in surrounding ground.

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 score0.886
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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