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Record W2270812803 · doi:10.1115/1.4032634

Design and Implementation of an Automated Gamma Probe for Jet Boring Uranium Mining

2016· article· en· W2270812803 on OpenAlexaffabout
Kasmet T. Niyongabo, Scott Nokleby

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsFirmwareDetectorDrillingRadiometric datingUraniumNuclear fuel cycleNuclear engineeringRemote sensingGeologyEnvironmental scienceComputer scienceEngineeringElectrical engineeringPhysicsComputer hardwareMechanical engineeringNuclear physicsFuel cycle

Abstract

fetched live from OpenAlex

A proof-of-concept detector prototype capable of collecting and storing radiometric data in the jet boring system (JBS) during pilot hole drilling at the Cigar Lake uranium mine is presented. Cigar Lake is the world’s second highest known grade uranium mine and is located in northern Saskatchewan, Canada. Variant design is used to design, develop, test, and implement the detector’s firmware, software, and hardware. The battery-powered detector is attached inside a JBS drill rod to collect radiometric data through the drilling cycle. A readout box is used to initiate the detector, recharge the battery, and download radiometric data after the pilot hole drilling cycle is complete. Functional testing results are presented, and comparative test results between the JBS gamma probe and the AlphaNUCLEAR Hi-Flux probe are evaluated. Field data collected from a pilot hole are plotted against the pilot hole’s driving layout and jetting recipe to show the accuracy of the readings collected.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.124

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 head0.010
GPT teacher head0.283
Teacher spread0.273 · 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 designBench or experimental
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
Published2016
Admission routes2
Has abstractyes

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