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
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».