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Industry Bibliographical Databases: Perspectives of Use in the Fmba of Russia for Scientific Expertise in Decision-Making. Report 2. Database on Health and Other Effects in Uranium Miners

2025· article· en· W4411559883 on OpenAlexaboutno aff
А. Н. Котеров, Л.Н. Ушенкова, T.M. Bulanova, N.A. Bogdanenko

Bibliographic record

VenueMedical Radiology and radiation safety · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsDatabaseUraniumComputer science

Abstract

fetched live from OpenAlex

The presented review of three reports is devoted to bibliographic databases on medical-biological and other effects and indexes in nuclear workers and uranium miners (U miners), developed within the framework of the research theme of the Federal Medical and Biological Agency of Russia and registered with the state in Rospatent. Report 1 outlined introductory issues of the theory of databases, as well as registers, and provided information on the database for nuclear workers. The presented Report 2 is devoted to the database for U miners. The purpose of creating the database for U miners was to form an accessible for abstract and full-text search repository of published data on topics relevant for conducting research examinations in the system of the Federal Medical and Biological Agency of Russia, in other healthcare institutions dealing with the radiation factor, and, more broadly, for conducting fundamental and applied research in the field of effects on miners as such and, specifically, on U miners. The database for U miners is uniform in relation to Russian and foreign research; the contribution of Russian/USSR publications (together with reports and hard-to-reach works) is 11%. The structural form of information is a catalog that includes primary (main) units of information in the form of an information file about the source (DOC), which contains the title of the publication/document, an abstract (sometimes additional information), and the full original publication (PDF, rarely HTML), available for 77 % of sources (there are 1009 sources in the database in total as of the beginning of February 2025). Among the 23 countries whose works made up the database, the largest contribution was made by the USA, the Czech Republic, Canada, Russia/USSR, Germany and France. Visual and/or software search of material in the database is supposed to be carried out both through the information titles of catalogs, including research themes carried out using the list of abbreviations (metadata for the database), and through all the texts of the sources included in the database using the proposed programs. The developed database has no analogues among industry databases/registers for U miners in various countries, nor among bibliographic and search systems. Through PubMed, Cochrane Library, EMBASE, CINAHL, INIS IAEA, Web of Science, eLibrary and even through Google, either several times fewer sources on the theme were found, or a much smaller number of publications in full originals than in the proposed database. The depth of the search for works on the effects and indexes for U miners in world search systems is significantly inferior to the developed database (1940–1950s versus 1920–1930s). It is concluded that the presented database on U miners is unique for examination within the framework of the Federal Medical and Biological Agency of Russia and other healthcare institutions, and has no complete replacement as a scientific reference and expert depot of sources.

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)0.004
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.029
GPT teacher head0.372
Teacher spread0.343 · 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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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