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Record W3136327142 · doi:10.31857/s2076673421010071

РЕКОНСТРУКЦИЯ БАЛАНСА МАССЫ ЛЕДНИКА САРЫ-ТОР ПО МЕТЕОРОЛОГИЧЕСКИМ ДАННЫМ

2021· article· ru· W3136327142 on OpenAlexaboutno aff
Victor Popovnin, A. S. Gubanov, Rysbek Satylkanov

Bibliographic record

VenueJournal Ice and Snow · 2021
Typearticle
Languageru
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Mass balance bn is the most important indicator of a glacier evolution. However, after the decay of the USSR direct measurements of bn performed in 1985–1989 in the Inner Tien Shan, including the Sary-Tor Glacier in Ak-Shiyrak Massif, had been desisted. As a result the available series of the data were limited 1989. Measurements in this area were renewed only in 2015. This paper is devoted to restoring the continuity of the mass-balance series over the period of the gap in measurements and extending this series down to 1929, i.e. to the beginning of regular meteorological observations on the reference HMS Tien Shan (3660 m a.m.s.l.). Accumulation was reconstructed using a linear relationship of bn with the air temperature and precipitation sum. Reconstruction of ablation was based on its cubic relationship with the temperature (modified Krenke– Khodakov formula) or on two-parameter linear approximation using the air temperature and wind velocity. Thereby, the decade of direct instrumental measurements (1984/85–1988/89 and 2014/15–2018/19) resulted in deriving and analyzing continuous 90-year-long series of annual values of bn and its constituents, analytical type of referent glacio-meteorological equations being assumed unchanged in time. Reconstruction for the Sary-Tor Glacier reveals a dominant trend towards the mass loss with rare and short-time episodes of retarding the negative tendencies. The comparison made with the long series of mass balance of other glaciers in Asia indicates a certain degree of synchronicity, which is slightly disturbed in recent years: the degradation of Sary Tor Glacier tends to progress more intensively. Conclusions about its evolution are particularly relevant in connection with the assumption about the impact of the Kyrgyz-Canadian gold mining company «Kumtor Gold Company» on local ecosystems against the background of its interest in expanding the mining zone to the bowels of the Earth under the tongue of this glaciological object.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.006

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 head0.028
GPT teacher head0.232
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2021
Admission routes1
Has abstractyes

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