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Record W1586418499 · doi:10.2172/769307

Idaho National Engineering and Environmental Laboratory Offsite Environmental Surveillance Program Report: Third Quarter 1999

2000· report· en· W1586418499 on OpenAlexaboutno aff
R. Evans

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceQuarter (Canadian coin)National laboratoryNuclear weaponEnvironmental monitoringAgency (philosophy)Environmental researchEnvironmental impact assessmentEnvironmental protectionEnvironmental planningEngineeringWaste managementEnvironmental engineeringGeographyPolitical scienceLawArchaeology

Abstract

fetched live from OpenAlex

The Environmental Science and Research Foundation conducts an offsite environmental surveillance program for the Department of Energy's Idaho National Engineering and Environmental Laboratory (INEEL). The Foundation's environmental surveillance program monitors the effects, if any, of US Department of Energy (DOE) activities on the offsite environment, collects data to confirm compliance with applicable environmental laws and regulations, and observes any trends in the environmental levels of radioactivity. This report for the third quarter of 1999 is based on 704 samples of air, fine particulates, atmospheric moisture, precipitation, milk, and food. All concentrations of radioactivity found in these samples were consistent with concentrations which have been found in sampling during recent quarters and which have been attributed in the past to natural background radiation, worldwide fallout from past nuclear weapons testing, and nuclear operations around the world. No! measured concentrations could be directly attributed to operations at the INEEL. Concentrations in all samples were below the guidelines set by both the DOE and the US Environmental Protection Agency (EPA) for protection of the public.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.201
Teacher spread0.196 · 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.

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
Published2000
Admission routes1
Has abstractyes

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