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Record W4318393132 · doi:10.1080/09553002.2023.2172623

Main radiation pathways in the landscape of Armenia

2023· review· en· W4318393132 on OpenAlexaff
V.B. Arakelyan, Garnik E. Khachatryan, A. G. Nalbandyan-Schwarz, Carmel Mothersill, Colin Seymour, Victoria L. Korogodina

Bibliographic record

VenueInternational Journal of Radiation Biology · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiotaNatural (archaeology)RadioresistanceClimate changeGeographyEcologyPhysical geographyEnvironmental scienceEarth scienceBiologyGeologyArchaeology

Abstract

fetched live from OpenAlex

PURPOSE: To investigate sources, accumulation, and vertical migration of radionuclides in Armenia, and their impact on biota. CONCLUSIONS: This review describes the radiation status in the landscape of Armenia and features of the impact of natural and human-generated radiation on human and non-human biotas, according to studies of Armenian scientists carried out since the middle of the last century. The mountain landscape demonstrates the diversity, speciation, and radioresistance of the biota, which arise under radiation exposure in a variable environment. Although the effects of radiation have been described for a long time, some of them require further study. It is important to present the data collected in order to produce a base line for future studies of radiation effects and interactions with other stressors caused by climate change.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.321
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2023
Admission routes1
Has abstractyes

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