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Trends in the cytogenetic and immunologic status of healthy persons; Kazakhstan, 2007–2022

2024· article· en· W4401832449 on OpenAlex
Oksana Cherednichenko, Georgij Demchenko, Unzira Kapysheva, Sh.K. Bakhtiyarova, A. L. Pilyugina, Dinara Azizbekova, Ulbosin Kozhaniyazova, Bolatbek Zhaksymov

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMutation Research/Genetic Toxicology and Environmental Mutagenesis · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMedical and Agricultural Research Studies
Canadian institutionsInstitute of Genetics
FundersMinistry of Education and Science of the Republic of Kazakhstan
KeywordsResidenceImmune statusImmune systemAntibodyEnvironmental healthGeographyBiologyDemographyImmunologyMedicineSociology

Abstract

fetched live from OpenAlex

Environmental pollution can affect immune health and genome stability. We have studied the immunological and cytogenetic status of healthy urban (Almaty City, which has high levels of air pollution) and rural residents of southern Kazakhstan, over the past 15 years. Differences between the groups in plasma immunoglobulin levels and chromosomal aberration frequencies were noted. Over the 15-year study period, decreases of immunoglobulin levels and increases of chromosomal aberration frequencies were observed and correlated with place of residence and ecological status of the region of residence; both ecological deterioration and the coronavirus pandemic are likely to have had negative effects. • Levels of chromosomal aberrations and immunoglobulins differed between urban and rural populations. • Deterioration of cytogenetic and immunologic status over time was observed. • A negative correlation was seen between total immunoglobulin content and frequency of chromosomal aberrations.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.382
Teacher spread0.322 · 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