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Record W6999956340

Ecological problems of middle Volga in the second half of the XXth century: Historical and ecological analysis of leading industrial regions development

2015· other· en· W6999956340 on OpenAlexaboutno aff

Bibliographic record

Venuezvestiya of the National Academy of Sciences of Belarus (National Academy of Sciences of Belarus) · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNatural (archaeology)Perspective (graphical)Natural resourceVolga regionEnvironmental degradationNatural heritage
DOInot available

Abstract

fetched live from OpenAlex

© 2015, Canadian Center of Science and Education. All rights reserved. The present article is aimed to identify origins and evolution of environmental problems characteristic for Middle Volga Region in the second half of the XXth century. The approach applied for the research allows to analyze the industrial growth of the country from a totally new level, to observe the course, character and peculiarities of its impact on the ecological degradation that determines the critical condition of environment at the present stage. The article reveals the results of historical and ecological analysis conducted by Russian and foreign researchers on issues of a human and environment interaction; they make it possible to designate for Russia such perspective scientific guidelines of studying contradictions in the system “human nature” as: origins and evolution of industrial pollution, ecological problems of urbanized territories, dynamics of natural resources exhaustion, water utilization history. The materials of this article may facilitate the efficient usage of economic, technological, moral and organizational methods aimed to impact the developing economic system, its highest ecologization.

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)0.017
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.010
Science and technology studies0.0000.017
Scholarly communication0.0000.001
Open science0.0060.001
Research integrity0.0010.001
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 head0.172
GPT teacher head0.328
Teacher spread0.156 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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