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Record W2997518761 · doi:10.24908/iqurcp.7467

Tracing the Migration of Low‐level Radioactive Waste Using Rn‐222 as an Indicator of Hydrogeological and Geochemical Conditions

2017· article· en· W2997518761 on OpenAlexvenueaboutno aff
Matthew N. Herod

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsnot available
Fundersnot available
KeywordsRadonRadioactive wasteHydrogeologyShoreWatershedEnvironmental scienceGroundwaterHydrology (agriculture)STREAMSGeologyContaminationRadioactive contaminationMining engineeringWaste managementGeotechnical engineeringOceanography

Abstract

fetched live from OpenAlex

Port Hope, Ontario, located on the north shore of Lake Ontario, is home to some of largest amounts of low‐level radioactive waste contamination in the world. The waste is enriched in 238U and 226Ra, both of which decay into the invisible, radioactive gas radon‐222 (222Rn). This project is an attempt to determine the amounts of 222Rn that have migrated from scattered waste sites into selected streams and groundwater in the local watershed. This knowledge can be used to predict hydrogeological and geochemical conditions within the sample stream and surrounding area.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.124
GPT teacher head0.376
Teacher spread0.252 · 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
Published2017
Admission routes2
Has abstractyes

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