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Influence of Environmental Conditions on the Susceptibility of the Territories to the Occurence of Forest Fires

2019· book-chapter· en· W2981674341 on OpenAlexaboutno aff
Olga Pasko, V.F. Kovyazin, Nadezhda Anatolyevna Lebedeva

Bibliographic record

VenueAdvances in environmental engineering and green technologies book series · 2019
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyZoningForest coverEnvironmental protectionRussian federationPhysical geographyEcologyRegional science

Abstract

fetched live from OpenAlex

The chapter describes the conditions of predisposition of territories to the emergence of forest fires on different continents of the world. Information on the types of forest fires and the characteristics of burning materials is given. Human and economic losses from the forest fires and other emergencies (earthquake, flood) are compared. The causes of forest fires and their dynamics in Europe, USA, Canada, Southeast Asia, and Russia are given in this chapter. An analysis of the factors of their occurrence is given. Forest fires in the Russian Federation, where they annually cover large areas, have been studied in detail. The dynamics of the burning of Russian forests in the regions and administrative districts of the Tomsk region is considered. The causes of fire emergence is revealed. The forecast of forest fires is given and zoning of forest areas of the region as for fire danger is carried out. The research identifies the role of natural conditions in the occurrence of forest fires at various territorial levels (continents, countries, regions, areas).

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.002
GPT teacher head0.169
Teacher spread0.166 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2019
Admission routes1
Has abstractyes

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