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Record W2013555238 · doi:10.1667/rr3222

Effects of Radiation on the Environment: A Need to Question Old Paradigms and Enhance Collaboration among Radiation Biologists and Radiation Ecologists

2004· article· en· W2013555238 on OpenAlexfundaboutno aff
Thomas G. Hinton, Joel S. Bedford, J. C. Congdon, F. W. Whicker

Bibliographic record

VenueRadiation Research · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsnot available
FundersCanadian Nuclear Safety Commission
KeywordsBiotaCommissionSet (abstract data type)Low Dose RadiationRadiation protectionEcologyEnvironmental ethicsEngineering ethicsComputer scienceBiologyPolitical scienceEngineeringMedicineLawNuclear medicine

Abstract

fetched live from OpenAlex

A historical perspective is given of the current paradigm that does not explicitly protect nonhuman biota from radiation but instead relies on the concept that if dose limits are set to protect humans, then the environment is automatically protected as well. We summarize recent international questioning of this paradigm and briefly present three frameworks for protecting biota that are being considered by the U.S. Department of Energy, the Canadian Nuclear Safety Commission, and the International Commission on Radiological Protection. We point out a controversial component in each of the three frameworks and suggest topics that need additional research. We emphasize that to properly address radiation protection of the environment, we need to understand how effects are integrated across different levels of biological organization. We caution that the proposed use of molecular end points to estimate ecological risks from radioactive contamination is applicable only if we understand the extent of the impact that molecular damage has on individual organisms and populations of exposed biota. To accomplish the latter, enhanced collaborations are required among the traditionally separate disciplines of radiation biology and radiation ecology.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.293
Teacher spread0.282 · 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 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

Citations26
Published2004
Admission routes2
Has abstractyes

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