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Record W2980023655 · doi:10.17721/1728-2721.2019.74.3

INDIGENOUS MINERAL DEPOSITS IN THE TABLE D. I. MENDELEEV: WORLD DIMENSION

2019· article· en· W2980023655 on OpenAlex
Alexander Beydik

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBulletin of Taras Shevchenko National University of Kyiv Geography · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsMineral resource classificationEarth scienceContext (archaeology)GeologyTable (database)IndigenousGeographyMineralGlobeGeochemistryArchaeologyEcology

Abstract

fetched live from OpenAlex

Geography of mineral deposits and the distribution of chemical elements on the globe are characterized by heterogeneity. Mineral resources of the world, mineral deposits are devoted to a large array of publications of domestic and foreign specialists – geologists, geographers, geochemists, economists. During the mastering of the material, comparative-geographical, cartographic (analysis of maps of mineral resources, mineral resources in the context of continents and regions of the world), monographic (fundamental works of leading domestic and foreign geologists and resource scientists, geological and mineral reference books and dictionaries, multi-volume editions, devoted to the geology and mineral resources of individual countries and regions of the world) methods, systematic approach, in the processing and systematization of data used modern no computer technology. The explored deposits of mineral raw materials (actual and potential) form on the planet as separate local deposits, as well as geochemical zones – areas where concentrated economically valuable chemical elements and their compounds (minerals and rocks) are diverse in genesis (origin), stocks, exploitation possibilities. The largest of them are Appalachians in the USA – Western Hemisphere, High Velt in South Africa, Hibiny and Ural in Russia – Eastern Hemisphere. Leading countries in the territory where most of the geochemical raw materials are mined from the bowels are the USA (65 % of the total number of elements of the table), Russia (48 %), China (38 %), Canada (38 %), South Africa (30 %), Australia (27 %), Kazakhstan (19 %), India (14 %), Mexico (13 %). Systematized representations about the level of provision of mineral raw materials and minerals of individual countries and territories of the world. D. I. Mendeleev’s table and its mineral raw materials are presented as an objective factor of the international geographical division of labour. The given data reveal an adequate level of provision of countries and territories with mineral resources. The highlighted problem has confirmed the high density of interdisciplinary connections (geography, geology, geochemistry, economics, regionalisms). The given data can be implemented in the latest programs of reformed education in Ukraine.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.004
GPT teacher head0.152
Teacher spread0.148 · 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