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Record W2782800699 · doi:10.1080/11956860.2017.1396100

Revegetation of areas disturbed by rocket impact in Central Kazakhstan

2017· article· en· W2782800699 on OpenAlexvenueno aff
Sergey Lednev, Tatyana Koroleva, П. П. Кречетов, Anna Sharapova, И. Н. Семенков, Andrey Karpachevskiy

Bibliographic record

VenueEcoscience · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsRevegetationVegetation (pathology)Environmental scienceDisturbance (geology)Ruderal speciesFalling (accident)Rocket (weapon)Plant communityPhysical geographyEcological successionEcologyGeographyGeologyHabitatBiologyArchaeology

Abstract

fetched live from OpenAlex

Rocket launches are a source of anthropogenic disturbance to Central Kazakhstan ecosystems. Multistage launch vehicles (LV) are used for orbit insertion of different spacecrafts from the Baikonur cosmodrome (Republic of Kazakhstan). The launch consists of stages during which the rocket separates successively, with pieces falling to the ground along the flight route of the LV. Regions of first stage falling located in Central Kazakhstan endure the most intensive impact. First stage fallings lead to mechanical and pyrogenic disturbance and pollution by fuel components. We characterized vegetation changes at the first stage falling sites of ‘Proton-M’ rocket carriers during two growing seasons. Spontaneous revegetation by ruderal plant communities occurs after falling. First stage falling sites have lower vegetation cover and species diversity. Ceratocarpus arenarius is a dominant species in plant communities at the sites that have been affected by first stage falling. After winter rocket launches vegetation is less deteriorated at the falling sites than after spring and summer launches. The recovery process in plant communities is considerably faster at falling sites corresponding to winter rocket launches.Nomenclature: S.K. Cherepanov (1995).

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 score0.015
Threshold uncertainty score0.274

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 studies0.0000.000
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 head0.006
GPT teacher head0.250
Teacher spread0.243 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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